Rockfish Historical Harvest Estimates

This project seeks to estimate sport fish harvest and releases of rockfish in Alaska waters by improving on the Howard et al. (2020) methods and expand the time series back to 1977 when the statewide harvest survey (SWHS) was first implemented. This is essentially a Bayesian version of the Howard methods that allows for more appropriate and defensible sharing of information between areas, handles missing data in a more appropriate manor, accurately propagates uncertainty throughout the estimation procedure and replaces the Howard decision tree approach to low sample sizes with a hierarchical model. The methods and results for generating harvest estimates are generally consistent between the Bayesian model and the Howard methods. Harvest estimates are consistent with Howard estimates during contemporary times, but may differ based on more appropriate weighting of SWHS and logbook data, including estimating and correcting bias in the SWHS data.

The Bayesian methods depart from the Howard method in how releases are estimated. The Howard methods assume that the species composition of the harvests are equal to the species composition of released fish, which is clearly contraindicated in the logbook data. For instance, logbook data demonstrates that yelloweye have been retained at high levels up until restrictions were enacted in recent years, whereas pelagic rockfish were released in significant numbers in the past with retention increasing in recent years as they have become more prized by anglers. Recent prohibition on retaining yelloweye in Southeast Alaska highlights the shortcomings of the original Howard assumptions as the species composition of the harvest would indicate that no yelloweye were caught and released during the closure.

The Howard method for estimating releases for private anglers also relied on an expansion of the logbook release estimates based on the ratio of private:guided releases of all rockfish in the SWHS. In addition to the faulty assumptions about species composition, this method ignores potential bias in SWHS estimates of harvests and releases or at least assumes that the bias in release and harvests are the same. As demonstrated in Figure 1, the bias in those two quantities appears to be quite different based on the logbook data. The Bayesian model thus attempts to estimate release probabilities based on the logbook data coupled with bias corrected estimates from the SWHS.

Lastly, the Howard methods were only used on data beginning in 1999 with the advent of the logbook program and estimates of harvests and releases prior to that have been based on linear ramps from 1999 back to the perceived start of the fishery. The Bayesian methods allow us to expand the time series back to 1977 when the SWHS was implemented by leveraging regional data trends in species composition and the proportion of caught rockfish harvested by species and/or species complex. Key advantages of the Bayesian approach are highlighted in table 1.

Table 1. Summary of key improvements in reconstructiing sport fish removals of rockfish using the Bayesian model as compared to the Howard et al. (2020) methods.

Issue	Howard	Bayes
Time series	1999 - present	1977 - present
Bias in SWHS	Not explicitly dealt with. Relies on logbook data and ratios of guided/unguided from SWHS data to estimate unguided releases and harvests.	Explicitly estimates bias in SWHS harvest and release estimates based on logbook data.
Species composition of releases	Assumes that species composition of releases is equal to that of the harvest, which is not evident in the logbook data.	Recognizes different release probabilities by species / species assemblage and estimates it from logbook data and bias corrected SWHS data
Sample size limitations	Uses sample size threshholds such that when areas fall below those threshholds values are borrowed from nearby areas.	Uses a hierarchichacal modelling approach that shares information between areas in the same region. Thus all data is used, even with small sample sizes. This is a more sound method that avoids assumptions and uses all of the data.
Error propogation	Error is propogated when variance estimates are available, but there is uncertainty associated with borrowing values from nearby areas, or the assumption of species compositions being identical in harvest and releases, are not dealt with.	By breaking the assumption that species composition is equal between harvests and releases, uncertainty in the release estimates is more reflective of the fishery. Furthermore, the hyerarchichal approach more accurately captures uncertainy within and between areas within a region.

Data

Harvest data was available for 22 commercial fishing management areas in Southcentral and Southeast Alaska. Areas with negligible rockfish harvest were pooled with adjacent areas for analysis. Specifically the Aleutian and Bering areas were pooled into an area labeled BSAI; the IBS and EKYT were pooled into an area labeled EKYKT; the Southeast, Southwest, SAKPEN and Chignik areas were pooled into an area labeled SOKO2PEN and the Westside and Mainland areas were pooled into an area labeled WKMA.

Stateside Harvest Survey (SWHS)

Statewide harvest survey estimates of rockfish catch and harvest are available for 28 years (1996-2023) for all users and for 13 years (2011-2023) for guided anglers (Figure 0). Additionally, there are overall harvest estimates from 1977- 1995 and release estimates from 1990-1995 that required some partitioning to ascribe to current management units. Harvests in unknown areas were apportioned based on harvest proportions in 1996. Variance estimates are not available for pre-1996 data and as such, the maximum observed coefficient of variation (cv) in each commercial fisheries management unit was applied to the pre-1996 values.

Figure 1.- Data sources for estimating rockfish harvests and releases in ADF&G commercial fisheries management units. Note that initial rockfish harvest estimates were not differentiated into species assemblage or species until 1998 when logbooks began differentiating by pelagic and non-pelagic. Logbooks began to collect data on yelloweye beginning in 2006. Port sampling programs to gather data on species composition of harvests began in 1996 in Southcentral and Kodiak and in 2006 in Southeast.

SWHS estimates are believed to be biased to some degree. These modelling efforts aim to estimate and correct for that bias with the assumption that logbook records are a census of guided harvests and releases.

SWHS Rockfish release estimates are inferred from the difference between catch and harvest estimates.

Adam noted that the first 5 years (23 years counting the historical data) in the SWHS data set for PWSO seem unreasonable (close to zero and not corroborated with logbook estimates). Adam recommended setting these harvests to unknown, but current model development has included the data. Once a satisfactory model has been identified we will exam the effects of censoring the PWSO data.

Creel Surveys

NA

Guide Logbooks

Sport fishing guides have been required to report their harvest of rockfish for 26 years (1998-2023). Reported harvest is also available by assemblage (pelagic vs. non-pelagic). Harvest of yelloweye and “other” (non-pelagic, non-yelloweye) rockfish were reported separately beginning in 2006.

Logbooks also record the number of rockfish released for the same categories. However, the reliability of the release data is somewhat questionable as reported releases are generally far lower than that estimated by the SWHS. As such several treatments of the data are considered.

Logbook versus SWHS estimates

Estimates of guided harvests and releases from the SWHS do not align with the census from charter logbooks. Logbook harvest reports are generally considered reliable and are used to assess the bias in SWHS reports. However, there is even greater disparity between release estimates in the two sources and it is debatable whether logbook releases should be treated as a census. The Howard et al. (2020) methods do treat the logbook release data as “true” and thus are considerably less than would be estimated from the SWHS data.

Figure 2.- SWHS harvest (left) and release (right) estimates from guided trips (x-axis) versus repoted harvests from charter logbooks (y-axis).

A note on model development

To evaluate the discrepancy in apparent bias in harvest and release data, several models were explored to estimate releases during model development. One method (\(LB_{fit}\)) considers the logbook release data to be reliable and a second method (\(LB_{cens}\)) treated the logbook release data as estimates of the minimum released, thus giving more weight to SWHS release estimates. A third method (\(LB_{hyb}\)) is a hybrid approach that treats reported releases of yelloweye as reliable but total rockfish and pelagic rockfish releases as minimums. Model development revealed a tension between the total and pelagic logbook releases and the yelloweye logbook releases. This tensions eventually highlighted the different release/retention probabilities between yelloweye and pelagics in the logbook data and prompted the current approach whereby that probability was calculated for the three main species complexes covered in the data: pelagics, yelloweye, and “other”. The methods described here follow the (\(LB_{fit}\)) formulation. Based on model behavior it is unlikely that the (\(LB_{cens}\)) model would work as there would not be enough data to estimate release probabilities. However, it may be worth running the (\(LB_{hyb}\)) approach as a sensitivity test at the very least.

Composition data

Harvest sampling data exists from Gulf of Alaska areas since 1996 and from Southeast Alaska areas since 2006. Port sampling data is comprised of the number of total rockfish, pelagic and non-pelagic rockfish, black rockfish and yelloweye rockfish. In Southeast Alaska, the number of Demersal Shelf Rockfish (DSR, of which yelloweye are one species) and slope rockfish are also recorded.

Process equations

The true harvest \(H_{ay}\) of rockfish for area \(a\) during year \(y\) is assumed to follow a temporal trend defined by a penalized spline:

\[\begin{equation} \textrm{log}(H_{ay})~\sim~\textrm{Normal}(f(a,y), {\sigma_H}) \end{equation}\]

where \(f(a,y)\) in a p-spline basis with 7 components (knots) and a second degree penalty. The variance, \(\sigma_H\), was given a normal prior with a mean and standard deviation of 0.25 and 1, respectively.

Charter and private harvest \(H_{ayu}\) (where u = 1 for charter anglers and u = 2 for private anglers) is a fraction of total annual harvest in each area:

\[\begin{equation} H_{ay1}~=~H_{ay}P_{(user)ay1}\\H_{ay2}~=~H_{ay}(1-P_{(user)ay1}) \end{equation}\]

where \(P_{(user)ay1}\) is the fraction of the annual harvest in each area taken by charter anglers. \(P_{(user)ay1}\) was modeled hierarchically across years as:

\[\begin{equation} P_{(user)ay1}~\sim~\textrm{beta}(\lambda1_a, \lambda2_a) \end{equation}\]

with non-informative priors on both parameters.

Annual black rockfish harvest \(H_{(black)ayu}\) for each area and user group is:

\[\begin{equation} H_{(black)ayu}~=~H_{ayu}P_{(pelagic)ayu}P_{(black|pelagic)ayu} \end{equation}\]

where \(P_{(pelagic)ayu}\) is the fraction of the annual harvest for each area and user group that was pelagic rockfish and \(P_{(black|pelagic)ayu}\) is the fraction of the annual harvest of pelagic rockfish for each area and user group that was black rockfish.

The southeast region also tracks two other non-pelagic rockfish assemblages, demersal shelf rockfish (DSR, which includes yelloweye) and slope rockfish. For the southeast region the harvest of those two assemblages is thus

\[\begin{equation} H_{(DSR)ayu}~=~H_{ayu}(1-P_{(pelagic)ayu})P_{(DSR|non-pelagic)ayu}\\ H_{(slope)ayu}~=~H_{ayu}(1-P_{(pelagic)ayu})P_{(slope|non-pelagic)ayu}\\ \end{equation}\]

where \(P_{(DSR|non-pelagic)ayu}\) and \(P_{(slope|non-pelagic)ayu}\) are the fractions of the annual harvest of non-pelagic rockfish for each area and user group that were DSR and slope rockfish, respectively.

Annual yelloweye rockfish harvest \(H_{(yelloweye)ayu}\) for each area and user group is calculated differently for central/Kodiak areas and southeast areas. For central and Kodiak areas yelloweye rockfish harvests are calculated as

\[\begin{equation} H_{(yelloweye)ayu}~=~H_{ayu}(1-P_{(pelagic)ayu})P_{(yelloweye|non-pelagic)ayu} \end{equation}\]

where \(P_{(yellow|non-pelagic)ayu}\) is the fraction of the annual harvest of non-pelagic rockfish for each area and user group that was yelloweye rockfish.

For southeast areas yelloweye harvests are a fraction of the DSR harvests such that

\[\begin{equation} H_{(yelloweye)ayu}~=~H_{(DSR)ayu}P_{(yelloweye|DSR)ayu} \end{equation}\]

The composition parameters \(P_{(comp)ayu}\), were modeled using a logistic curve that would allow hindcasting without extrapolating beyond the limit of observed values such that:

\[\begin{equation} \textrm{logit}(P_{(comp)ayu})~=~\beta0_{(comp)ayu} + \frac{\beta1_{(comp)ayu}}{(1 + exp(\beta2_{(comp)ayu}*(y - \beta3_{(comp)ayu})))} + \beta4_{(comp)ayu}*I(u=private)+re_{(comp)ayu} \end{equation}\]

where the \(\beta\) parameters define the intercept, scaling factor, slope, inflection point and private angler effect, respectively, \(y\) is the year index, \(I(u=private)\) is an index variable which is 1 when the user groups is private and 0 otherwise and \(re_{(comp)ayu}\) is a random effect with a non-informative prior. \(\beta\) parameters were modeled hierarchically by region. When \(\beta\) parameters were inestimable as a result of no discernible change in composition over the observed time period. \(\beta1\) (scaling factor) and \(\beta2\) (slope) were fixed to 0 so that the long term mean value was used for hindcasting.

The true number of released rockfish \(R_{ayu}\) were based on the proportion of the total catch harvested, \(pH_{(comp)ayu}\), by area, year, user group and species grouping. Because release data from the SWHS is for all rockfish and the release data from logbooks is only subdivided into pelagics, yelloweye and “other” (non-pelagic, non-yelloweye), we only estimated \(pH_{(comp)ayu}\) for those categories. Thus, converting \(H_{(comp)ayu}\) to total catches by user group, \(C_{(comp)ayu}\), with \(pH_{(comp)ayu}\) results in estimates of total releases such that

\[\begin{equation} R_{(comp)ayu}~=~ C_{(comp)ayu} - H_{(comp)ayu} ~=~ \frac{H_{(comp)ayu}}{pH_{(comp)ayu}} - H_{(comp)ayu} \end{equation}\]

with total releases equal to the sum of the compositional releases. For non-yelloweye DSR and Slope rockfish assemblages in Southeast Alaska \(R_{(DSR)ayu}\) and \(R_{(slope)ayu}\) were estimated from \(R_{(other)ayu}\) using the species composition data from the harvest, thus assuming that slope and DSR assemblages were caught and released at the same rates.

The proportion harvest parameters for \(pH_{(comp)ayu}\) were modeled using a logistic curve that would allow hindcasting based on trends in the data without extrapolating beyond the range of observed values such that

\[\begin{equation} \textrm{logit}(pH_{(pH)ayuc})~=~\beta0_{(pH)ayu} + \frac{\beta1_{(pH)ayuc}}{(1 + exp(\beta2_{(pH)ayuc}*(y - \beta3_{(pH)ayuc})))} + \beta4_{(pH)ayuc}*I(u=private)+re_{(pH)ayuc} \end{equation}\]

A random effect term allowed estimation during the historical period when data is available, but the curve defined by the above equation determined release estimates between 1977 and 1990. As with the compositional trends, \(\beta\) parameters were modeled hierarchically by region. When \(\beta\) parameters were inestimable as a result of no discernable change in harvest probability over the observed time period, \(\beta1\) (scaling factor) and \(\beta2\) (slope) were fixed to 0 so that the long term mean value was applied.

Release mortality (i.e., the number of released rockfish expected to die) was calculated assuming fixed mortality rates developed in each of the regions. Deep water release (DWR) devices were mandated for charter fleets in 2013 and rates were derived from CITATION. Southeast applies basic rates estimated in these studies while Southcentral and Kodiak rates were derived by using historical depth-of-release data to adjust the rates based on area and user group.

The total number of mortalities by year, area, user and species/species assemblage in numbers was calculated by summing harvests and release mortality such that

\[\begin{equation} M_{(comp)ayu}~=~ H_{(comp)ayu} + m_{R-(comp)ayu} * R_{(comp)ayu} \end{equation}\]

where \(m_{R-(comp)ayu}\) is the release mortality rate by year, area, user and species (Figure XX).

Total removals in biomass were converted using the average weight of fish from port sampling?. A minimum sample size per year of X fish was used as the cutoff for including in the data set. Weights were modeled hierarchically to estimate weights in years when data was missing. The total biomass of removals by year, area, user and species was thus

\[\begin{equation} B_{(comp)ayu}~=~ \overline{wt}_{(comp)ayu} * M_{(comp)ayu} \end{equation}\]

where \(\overline{wt}_{(comp)ayu}\) is the mean weight by species, area, user and year.

Observation equations

SWHS estimates of annual rockfish harvest \(\widehat{SWHS}_H{ay}\) were assumed to index true harvest:

\[\begin{equation} \widehat{SWHS}_H{ay}~\sim~\textrm{LogNormal}\left(\textrm{log}(H_{ay}b_{ay}), \sigma_{SWHSHay}^2\right) \end{equation}\]

where bias in the SWHS harvest estimates \(b_H{ay}\) is modeled hierarchically across years as:

\[\begin{equation} b_H{ay}~\sim~\textrm{Normal}(\mu_H{(b)a}, \sigma_H{(b)a}) \end{equation}\]

with non-informative priors on both parameters.

SWHS estimates of guided angler harvest \(\widehat{SWHS}_H{ay1}\) are related to total harvest by:

\[\begin{equation} \widehat{SWHS}_H{ay1}~\sim~\textrm{LogNormal}\left(\textrm{log}(H_{ay1}b_{ay}), \sigma_{SWHS_{ay1}}^2\right) \end{equation}\]

Reported guide logbook harvest \(\widehat{LB}_H{ay}\) is related to true harvest as:

\[\begin{equation} \widehat{LB}_H{ay}~\sim~\textrm{Poisson}(H_{ay1})\\ \widehat{LB}_H{(pelagic)ay}~\sim~\textrm{Poisson}(H_{ay1}P_{(pelagic)ay1})\\ \widehat{LB}_H{(yelloweye)ay}~\sim~\textrm{Poisson}(H_{(yelloweye)ay1})\\ \widehat{LB}_H{(nonpel,nonye)ay}~\sim~\textrm{Poisson}(H_{(nonpel,nonye)ay1})\\ \end{equation}\]

Note that for central and Kodiak areas \(H_{(nonpel,nonye)ay1}\) is equal to the total harvest minus pelagic and yelloweye harvests. For southeast areas \(H_{(nonpel,nonye)ay1}\) is equal to the sum of the DSR and slope harvests minus yelloweye harvests.

SWHS estimates of annual rockfish releases \(\widehat{SWHS}_R{ay}\) were assumed to index true releases in a similar fashion and thus modeled similarly. As such, the release data are related to true releases just as harvests were modeled such that:

\[\begin{equation} \widehat{LB}_R{ay}~\sim~\textrm{Poisson}(R_{ay1})\\ \widehat{LB}_R{(pelagic)ay}~\sim~\textrm{Poisson}(R_{ay1}P_{(pelagic)ay1})\\ \widehat{LB}_R{(yelloweye)ay}~\sim~\textrm{Poisson}(R_{(yelloweye)ay1})\\ \widehat{LB}_R{(nonpel,nonye)ay}~\sim~\textrm{Poisson}(R_{(nonpel,nonye)ay1})\\ \end{equation}\]

Because logbook release data is more questionable and demonstrates greater disagreement with SWHS estimates (Figure 1), a second approaches was considered that loosened the assumption that logbook releases were a census. Methods explored to develope \(LB_{hyb}\) and \(LB_{cens}\) models are detailed at the end of this section.

SWHS estimates of guided angler release \(\widehat{SWHS}_R{ay1}\) is modeled the same as harvests.

SWHS release bias was modeled independently of the harvest bias \(b_H{ay}\) such that

\[\begin{equation} b_R{ay}~\sim~\textrm{Normal}(\mu_R{(b)a}, \sigma_R{(b)a}) \end{equation}\]

where bias in the SWHS release estimates \(b_R{ay}\) is modeled hierarchically across years as:

\[\begin{equation} b_R{ay}~\sim~\textrm{Normal}(\mu_R{(b)a}, \sigma_R{(b)a}) \end{equation}\]

with non-informative priors on both parameters.

The number of pelagic rockfish sampled in harvest sampling programs \(x_{(pelagic)ayu}\) follow a binomial distribution:

\[\begin{equation} x_{(pelagic)ayu}~\sim~\textrm{Binomial}(P_{(pelagic)ayu}, N_{ayu}) \end{equation}\]

where \(N_{ayu}\) is the total number of rockfish sampled in area \(a\) during year \(y\) form user group \(u\). The number of black rockfish sampled in harvest sampling programs was thus a proportion of the pelagic harvests

\[\begin{equation} x_{(black)ayu}~\sim~\textrm{Binomial}(P_{(black)ayu}, N_{ayu}^{pel}) \end{equation}\]

Yelloweye rockfish in Southcentral and Kodiak were modeled similarly as a proportion of the total number of non-pelagics such that

\[\begin{equation} x_{(yellow_{R2})ayu}~\sim~\textrm{Binomial}(P_{(yellow_{R2})ayu}, N_{ayu}^{nonpel}) \end{equation}\]

Southeast areas have several other non-pelagic groupings such that DSR and slope rockfish are a proportion of non-pelagics

\[\begin{equation} x_{(DSR)ayu}~\sim~\textrm{Binomial}(P_{(DSR)ayu}, N_{ayu}^{nonpel}) \end{equation}\]

and

\[\begin{equation} x_{(slope)ayu}~\sim~\textrm{Binomial}(P_{(slope)ayu}, N_{ayu}^{nonpel}) \end{equation}\]

with yelloweye in southeast a proportion of the DSR harvest

\[\begin{equation} x_{(yellow_{R1})ayu}~\sim~\textrm{Binomial}(P_{(yellow_{R1})ayu}, N_{ayu}^{DSR}). \end{equation}\].

Kodiak has limited port sampling beyond the main harbors but has a robust hydroacoustic survey that is used to quantify black rockfish abundance across the management area and uses stereocameras to derive species compositions of the hydroacoustic data. This data was used as supplementary data to further inform the model to the proportion of pelagic rockfish that are black in Kodiak areas. Angler landings in Kodiak show a higher proportion of black rockfish relative to the hydroacoustic survey and thus the proportion of black rockfish in the hydroacoustic sample related to the true proportion such that

\[\begin{equation} P_{(black|pelagic)ayu}^{HA} ~\sim~ P_{(black|pelagic)ayu} + ae_{au} \end{equation}\].

where \(ae_{au}\) is the angler effect for each area and user group modeled hierarchically around a mean of 0. Predicted \(P_{(black|pelagic)ayu}^{HA}\) assumed a beta distribution such that

\[\begin{equation} P_{(black|pelagic)ayu}^{HA} ~\sim~ beta(\alpha_{HA},\beta_{HA}) \end{equation}\]

where

\[\begin{equation} \alpha_{HA} ~=~ (P_{(black|pelagic)ayu}^{HA})^2 * \frac{1 - P_{(black|pelagic)ayu}^{HA}}{\frac{var_{P_{HA}}-1}{P_{(black|pelagic)ayu}^{HA}}}, \end{equation}\]

\[\begin{equation} \beta_{HA} ~=~ (\alpha_{HA}) * \frac{1}{P_{(black|pelagic)ayu}^{HA} - 1}, \end{equation}\]

\[\begin{equation} var_{P_{HA}} ~=~ (P_{(black|pelagic)ayu}^{HA} * cvP_{(black|pelagic)ayu}^{HA})^2 \end{equation}\]

where \(cvP_{(black|pelagic)ayu}^{HA}\) is the coefficient of variation for the hydroacoustic proportions

\[\begin{equation} cvP_{(black|pelagic)ayu}^{HA} ~=~ \frac{\sqrt{varP_{(black|pelagic)ayu}^{HA}}}{P_{(black|pelagic)ayu}^{HA}} \end{equation}\]

and the variance is approximated using the XXXX method as

\[\begin{equation} varP_{(black|pelagic)ayu}^{HA} ~=~ (\frac{1}{n_{pel}})^2 * varN_{black} + (\frac{n_{black}}{n_{pel}^2}) * varN_{pel} \end{equation}\]

where \(varN_{black}\) and \(varN_{black}\) are the variance of the estimated number of black and pelagic rockfish in the hydroacoustic survey, respectively (CITATION).

The average weight of rockfish by species, user, area and year was modeled hierarchically at several levels within regions such that

\[\begin{equation} wt_{(comp)ayu} ~\sim~ Normal(wt_{(comp)au},\sigma_{wt_{(comp)au}}) ~\sim~ Normal(wt_{(comp)a},\sigma_{wt_{(comp)a}}) ~\sim~ Normal(wt_{(comp)region},\sigma_{wt_{(comp)region}}) \end{equation}\]

where region refers to Kodiak, Southcentral and Southeast. Mean weights and variance were calculated as XXX.

Alternative likelihoods for release estimates

To loosen the assumption that logbook release data are an effective census of true releases I explored models that treated logbook release estimates as a lower bound on the estimate of true releases. In a hybrid approach yelloweye and non-pelagic releases are regarded as a reliable census (given the emphasis and ease of recording these fish) but censors the pelagic and total rockfish release estimates (where censoring implies NA values) such that

\[\begin{equation} \text{censored} \widehat{LB}_R{ay}~\sim~\textrm{LogNormal}\left(\log(R_{ay}), 1\right)\text{T}\left(\widehat{LB}_R{ay}, \infty\right) \\ \text{censored} \widehat{LB}_R{(pelagic)ay}~\sim~\textrm{LogNormal}\left(\log(R_{(pelagic)ay}), 1\right)\text{T}\left(\widehat{LB}_R{(pelagic)ay}, \infty\right) \\ \widehat{LB}_R{(yelloweye)ay}~\sim~\textrm{Poisson}(R_{(yelloweye)ay1})\\ \widehat{LB}_R{(nonpel,nonye)ay}~\sim~\textrm{Poisson}(R_{(nonpel,nonye)ay1})\\ \end{equation}\]

This model formulation failed such that there was not enough data to inform pelagic releases and the values did not seem valid. A second approach is being explored that fits the censored data using a lognormal distribution centered around the logbook release value, but also with a lower bound equal to the number of recorded releases such that

\[\begin{equation} \widehat{LB}_R{ay}~\sim~\textrm{LogNormal}\left(\log(R_{ay}), \sigma_{Ray1}^2\right)\text{T}\left(\widehat{LB}_R{ay}, \infty\right) \\ \widehat{LB}_R{(pelagic)ay}~\sim~\textrm{LogNormal}\left(\log(R_{(pelagic)ay}), \sigma_{Ray1}^2\right)\text{T}\left(\widehat{LB}_R{(pelagic)ay}, \infty\right) \\ \widehat{LB}_R{(yelloweye)ay}~\sim~\textrm{Poisson}(R_{(yelloweye)ay1})\\ \widehat{LB}_R{(nonpel,nonye)ay}~\sim~\textrm{Poisson}(R_{(nonpel,nonye)ay1})\\ \end{equation}\]

Logbook data is assumed to be a census and as such there is no estimate of uncertainty. As of this writing, several methods are being examined for how to treat \(\sigma_{Ray1}^2\). Models are being run that attempt to allow the model to estimate \(\sigma_{Ray1}^2\) with priors. A simple model applies a uniform prior (0.1,50) to \(\sigma_{Ray1}^2\). A hierarchichal approach based on regions is also being examined whereby \(\sigma_{Ray1}^2\) is lognormally distributed around hyper priors \(\mu_{\sigma_R}\) and \(\sigma_{\sigma_R}\). Initial efforts have applied a uniform prior on \(\mu_{\sigma_R}\) between 1 and 50 and on \(\sigma_{\sigma_R}\) between 0 and 10.

Priors.

Priors range from uninformative to very informative or fixed. Priors for compositional logistic parameters are in Table 2 and proportion harvest logistic parameters are in Table 3. Until I figure out how to make a nice table in Rmarkdown, please refer to the attached spreadsheet and comp and harvp tabs.

Unresolved issues and outstanding questions:

1. Reliability of unguided release estimates: These estimates have the least information feeding them and rely on the bias-corrected SWHS release estimates of all rockfish and the trends in release probability evident in the logbook data. The \(\beta4\) term that estimates the guided/unguided effect was given a very informative prior that tied the release probability of private anglers tightly to that of the charter fleet. The model is then trying to balance the three species complex estimates (pelagic, yelloweye and other) so that they sum to the total unguided releases estimated from the bias corrected SWHS data. For the most part this seems reasonable and appears to work, but there are certain areas where the estimates are “wonky”:

   1. Total rockfish releases more or less align with the total releases estimated with the Howard methods. Presumably, much of the discrepancy results from the substantial bias in release estimates from the SWHS. Interestingly, the logbook data indicates that the SWHS underestimates harvests but overestimates releases by a significant factor (Figure 23 and 24 below).
   2. In general, release estimates of black rockfish are substantially lower than those calculated using the Howard methods. Presumably, much of this derives from the bias correction of the SWHS release estimates.
   3. Yelloweye release estimates also differ considerably from the Howard estimates, but unlike black rockfish are sometimes lower and sometimes higher. Two areas in particular are a little head scratching. Yelloweye releases in the Kodiak Northeast area in particular are significantly lower than for guided anglers with the same pattern evident in Cook Inlet to a lesser extent. Cook Inlet yelloweye numbers are very small, so this is a sample size issue with little consequence. The cause of the Kodiak northeast estimates is not clear to me at this point, but the model estimates the proportion harvested by unguided anglers to be much lower than that of guided anglers, even with the informative prior on \(\beta4\). This must be a product of the bias corrected SWHS release estimates and how the model is partitioning that estimate into the 3 species complexes, but itis a bit a of head scratcher.

2. Proportion guided estimates: There is not much data on this proportion prior to 2011 and it is not modeled with any sort of trend as was done for species composition and harvest proportions. With the exception of Cook Inlet and North Gulf Coast areas, there is little, if any, trend apparent in the data and perhaps this approach is the best available given the data available. However, if there are data sources somewhere that could inform this part of the model they could be incorporated.

3. Prior choices in general need to be vetted. The priors on the logistic curves are fairly informed in an effort to achieve the desired shapes for hindcasting. Ideally, sensitivity testing would occur but the model is very slow to converge. The beta parameters on the logistic curves have required a lot of work on the priors to reach convergence.

4. Proportion harvest estimates for non-pelagic, non-yelloweye in Kodiak WKMA: I need to adjust the prior on the inflection point, \(\beta3\), so that it is forced to occur after 2006. Right now the model is estimating inflection in two Kodiak areas before that point where there is no data to justify a shift. The current inflection is a result of the hierachichal model.

5. Proportion pelagic in PWS and CSEO: The parameters for these particular proportions are very slow to converge. For the CSEO, the estimates of the \(\beta\) parameters are similar to the other Southeast areas, but the mixing is poor over the length of the chains. In this case I think they will ultimately converge with a very long model run and the shape of the curve in the model output looks acceptable. For the two PWS areas the model seems to struggle with the disparate proportional data from the logbook and the port sampling. There is some wandering in the chains of the \(\beta0\) and \(\beta1\) terms and spikiness in the \(\beta2\) terms. I’ve been working on constraining the hyperpriors for PWS \(beta2\). Similar to CSEO, it may just entail a very long model run to reach convergence, but the shape of the curves looks reasonable.

Next steps:

Once the model is finalized, harvest and release numbers need to be converted into biomass removals. This is a two step process where release mortality estimates are applied to the release estimates to estimate the number of released rockfish that do not survive. This is based on studies and will reflect the values that the department has been using with the Howard methods. Region 2 (both Southcentral and Kodiak) have release-at-depth estimates from a number of years that they apply across all years and then calculate mortality rates based on those estiates. Southease does not have release-at-depth data and simply applies an assumed rate based on research.

Once release mortality is calculated average weight data is applied to convert numbers to biomass. The plan is to incorporate all of this into the model to propogate uncertainty into the posteriors. However, the model already takes a long time to run and I may explore a simpler approach using the posteriors from the numbers model to speed up processing.

Results

• Model: LB_fit_3pH

• Model Run: *Gen3aa_indcomp_no_swhs_rel_FULL_thru2023_5e+06__2025-08-26* (Naming convention: modelname_thruYEAR_iters_rundate)

• Proportion of parmaters converged (Rhat <= 1.1): 0.9878

• See end of document for summary of unconverged parameters.

Figure X.- Rhat values and proportion of parameters that converged (Rhat < 1.1.)

Estimate comparison

Since previous estimates of rockfish harvest have been produced these first 3 graphs will be used to show how the modeled estimates compare to the estimates produced earlier. For total rockfish the estimates are in general agreement although differences are noted. These estimates should be more reliable because they include both SWHS and guide logbook data, handle variance more appropriately, use hierarchical distributions when data is missing, directly consider observation error and are produced using reproducible research.

Figure 3.- Total rockfish harvests 1996-2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 3.- Total rockfish releases 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Notes from Adam: When looking at only black rockfish the most significant differences are for the Prince William Sound Inside area. I did not spend a great deal of time tracking this down although it looks like the previous version used bad values for \(P_{(black)ayu}\) for at least unguided anglers. For the moment I would ignore the results for BSIA and SOKO2SAP. I think it is possible to give approximate values for these areas but it will require a little more coding which I have yet to do.

Figure 4.- Black rockfish harvests 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

And black rockfish releases…

Figure 5.- Black rockfish releases 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 6.- Yellow rockfish harvests 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 7.- Yellow rockfish releases 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 8.- DSR rockfish (excluding yelloweye) harvests 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 9.- DSR rockfish releases (including yelloweye) 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 11.- Slope rockfish harvests 1996-2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 12.- Slope rockfish releases 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Total Biomass Removal Estimates

Figure 13.- Black rockfish estimated total removals in lbs in 1996–2023. Total removals are calculated from the harvests, the estimated release mortality and mean fish weights. Error polygons represent 95% confidence intervals.

Figure 14.- Yellow rockfish estimated total removals in lbs in 1996–2023. Total removals are calculated from the harvests, the estimated release mortality and mean fish weights. Error polygons represent 95% confidence intervals.

Figure 15.- Pelagic rockfish estimated total removals in lbs in 1996–2023. Total removals are calculated from the harvests, the estimated release mortality and mean fish weights. Error polygons represent 95% confidence intervals.

Figure 16.- Non-yelloweye, demersal shelf rockfish estimated total removals in lbs in 1996-2023. Total removals are calculated from the harvests, the estimated release mortality and mean fish weights. Error polygons represent 95% confidence intervals.

Figure 17.- Slope rockfish estimated total removals in lbs in 1996-2023. Total removals are calculated from the harvests, the estimated release mortality and mean fish weights. Error polygons represent 95% confidence intervals.

Model fit

Logbook residuals

Figure 18.- Residuals from logbook harvests.

SWHS residuals

Figure 19.- Residuals from SWHS harvests.

Figure 20.- Residual of SWHS releases.

Parameter estimates

P(Charter)

These histograms show the posterior distribution of the mean percent of rockfish harvested by the charter fleet.

Figure 21.- Mean percent of harvest by charter anglers.

When considered annually we see the percent of rockfish harvested by the charter fleet follows our data fairly well although the model smooths out the changes and we just do not have much information about this ratio. Prior to 2011 the percent charter is confounded with SWHS bias and should be mostly discounted.

Figure 22.- Annual estimates of the percent of harvest by charter anglers for 16 commerical fishing manamgent areas, 1996-2023.

P(Harvest)

These plots show the fitted logistic line to the proportion of caught rockfish that are harvested. These estimates are used for hindcasting catch estimates based on the harvest data in early years when catch estimates are unavailable.

Figure 23.- Annual proportion of pelagic rockfish catch that was harvested. Note that pre-1990 estimates are used to estimate catch in these years when catch estimates are not available.

Figure 24.- Annual proportion of yelloweye rockfish catch that was harvested. Note that pre-1990 estimates are used to estimate catch in these years when catch estimates are not available.

Figure 25.- Annual proportion of non-pelagic, non-yelloweye rockfish catch that was harvested. Note that pre-1990 estimates are used to estimate catch in these years when catch estimates are not available. Note, that this is not estimated for Southeast areas because non=pelagics are divided between DSR (including yelloweye) and Slope species.

## NULL

## NULL

SWHS bias

Figure 23 shows the mean estimate for SWHS bias in harvests and releases. Cook Inlet, North Gulf Coast and North Southeast Inside all look pretty good while most other areas have substantial bias. Prince William Sound Inside has the largest bias. Bias in release estimates is substantial and whereas the SWHS appears to underestimate harvests, it appears to greatly overestimates releases by a factor of 2 or more in most areas as derived from logbook reported releases.

Figure 28.- Mean SWHS bias for harvests and catches. Note that a bias < 1 indicates that the SWHS underestimates the true value and bias > 1 indicates the survey overestimates the true value.

Our estimates of SWHS harvest bias track observations fairly well when he have guided harvest estimates. The estimates of release bias in the SWHS data track observed patterns to an extent, but appear to smooth these more volatile disagreements with the logbook data. Adam postulated in his initial start on this that some of this could be the result of the estimates of the proportion guided. This value was not modelled with a trend and thus applies a constant estimate when hindcasting. Data on these relationships could greatly improve this model.

Figure 29.- Annual estimates of SWHS bias in harvests and releases for 16 commerical fishing manamgent areas, 1996-2023. Note that a bias < 1 indicates that the SWHS underestimates the true value and bias > 1 indicates the survey overestimates the true value.

P(pelagic)

We model the percentage of pelagic rockfish in the harvest because we have the information for charter anglers (via logbooks) starting in 1998. Other than looking at the model estimates you can use Figure 25 to compare the two data streams for pelagic rockfish harvest. In general they are in agreement with major exceptions in Price William Sound inside, Prince William Sound outside (early in the time series) and South Southeast inside.

Figure 30.- Annual estimates of the percent of the sport harvest that was pelagic rockfish for 16 commerical fishing manamgent areas, 1996-2023.

P(black|pelagic)

Note that in Southeast Alaska we only have composition data starting in 2006. Tania dug up old SE data, but it did not provide any useful data for species apportionment. For the most part, P(black|pelagic) is relatively constant across areas, with the exception of Cook Inlet and NSEI in Southeast AK. It may be worth discussing whether the shifts in those areas is a result of improved or changing species identification rather than actual shift in the species composition of the catch.

Figure 31.- Annual estimates of the percent of the sport harvest of pelagic rockfish that were black rockfish for 16 commerical fishing manamgent areas, 1996-2023. Kodiak panels include data from a hydroacoustic survey and the proportion of pelagic rockfish that are black in those areas (red) and the adjusted proportions based on obseved harvests for charter (blue) and private (cyan) users.

P(yelloweye|non-pelagic / yelloweye|DSR)

Figure 32.- Annual estimates of the percent of the sport harvest of non-pelagic rockfish that were yelloweye rockfish for 16 commerical fishing manamgent areas, 1996-2023. Note that P(yelloweye) is the the proportion relative to non-pelagics for Central and Kodiak areas but is relative to DSR for Southeast areas.

P(DSR|non-pelagic)

Figure 33.- Annual estimates of the percent of the sport harvest of non-pelagic rockfish that were DSR rockfish for 6 Southeast commerical fishing manamgent areas, 1996-2023.

P(slope|non-pelagic)

Figure 34.- Annual estimates of the percent of the sport harvest of non-pelagic rockfish that were slope rockfish for 6 southeast commerical fishing manamgent areas, 1996-2023. Note that P(yelloweye) is the the proportion relative to non-pelagics for Central and Kodiak areas but is relative to DSR for Southeast areas.

P(slope|non-pelagic & non-yellowye) For release estimates

Figure 35.- Annual estimates of the percent of the sport non-pelagic, non-yelloweye releases that were slope rockfish for 6 southeast commerical fishing manamgent areas, 1996-2023.

Weight Fits

Figure 36.- Mean weights of black rockfish used to estimate biomass from harvest and release mortality estimates in numbers of fish.

Figure 37.- Mean weights of yelloweye rockfish used to estimate biomass from harvest and release mortality estimates in numbers of fish.

Figure 38.- Mean weights of non-black, pelagic rockfish used to estimate biomass from harvest and release mortality estimates in numbers of fish.

Figure 39.- Mean weights of non-yelloweye, demersal shelf rockfish used to estimate biomass from harvest and release mortality estimates in numbers of fish.

Figure 40.- Mean weights of slope rockfish used to estimate biomass from harvest and release mortality estimates in numbers of fish.

### Summary of unconverged parameters:

Table X. Unconverged parameters.

area	variable	year	user	species	Rhat
BSAI	tau_prigui_pre				1.291016
BSAI	Rp_ayu	1			1.288801
BSAI	R_ayu	1			1.288800
BSAI	Rp_ay	1			1.288744
BSAI	R_ay	1			1.288742
BSAI	Rb_ayu	1			1.288696
BSAI	Rb_ay	1			1.288636
BSAI	R_ayu	4			1.278203
BSAI	Rp_ayu	4			1.278195
BSAI	Rb_ayu	4			1.278087
BSAI	Rp_ay	4			1.275048
BSAI	R_ay	4			1.275003
BSAI	Rb_ay	4			1.274904
BSAI	Hb_ayg	3			1.268206
BSAI	R_ayu	11			1.266908
BSAI	Rp_ayu	11			1.266904
BSAI	Rp_ay	11			1.266719
BSAI	R_ay	11			1.266718
BSAI	H_ayg	3			1.266065
BSAI	Hp_ayg	3			1.265995
BSAI	Rb_ayu	11			1.263335
BSAI	Rb_ay	11			1.263175
BSAI	Ro_ayg	3			1.263172
BSAI	Hy_ayu	15			1.262623
BSAI	Ho_ayg	3			1.260787
BSAI	Hy_ay	15			1.260045
BSAI	Hy_ayg	3			1.255793
BSAI	Rb_ayu	9			1.250694
BSAI	R_ayu	9			1.250280
BSAI	Rp_ayu	9			1.250278
BSAI	Rb_ay	9			1.248606
BSAI	Rp_ay	9			1.248131
BSAI	R_ay	9			1.248118
BSAI	Ro_ay	3			1.247216
BSAI	Rp_ayu	2			1.234543
BSAI	R_ayu	2			1.234531
BSAI	Ro_ayu	3			1.234469
BSAI	Rb_ayu	2			1.234070
BSAI	Rp_ay	2			1.232400
BSAI	R_ay	2			1.232368
BSAI	Ro_ayu	11			1.231970
BSAI	Rb_ay	2			1.231950
BSAI	Rb_ayu	5			1.231103
BSAI	R_ayu	5			1.230037
BSAI	Rp_ayu	5			1.230018
BSAI	Rb_ay	5			1.226114
BSAI	Rp_ay	5			1.224671
BSAI	R_ay	5			1.224665
BSAI	Ro_ay	11			1.221633
BSAI	Ro_ayu	2			1.219449
BSAI	Ho_ay	10			1.211405
BSAI	Ho_ayu	10			1.210856
BSAI	Ry_ayg	3			1.201814
BSAI	Rb_ayu	8			1.199759
BSAI	R_ayu	8			1.199038
BSAI	Rp_ayu	8			1.199019
BSAI	Rb_ay	8			1.198546
BSAI	Rp_ay	8			1.197791
BSAI	R_ay	8			1.197774
BSAI	Rp_ayu	17			1.195497
BSAI	R_ayu	17			1.195373
BSAI	Rb_ayu	17			1.195305
BSAI	Ro_ay	2			1.191194
BSAI	Hb_ay	3			1.190191
BSAI	Rb_ay	17			1.189041
BSAI	Rp_ay	17			1.188420
BSAI	R_ay	17			1.188194
BSAI	Hp_ay	3			1.186316
BSAI	Ry_ayu	3			1.181717
BSAI	Ry_ay	3			1.181531
BSAI	Rb_ayg	3			1.176878
BSAI	H_ay	3			1.176200
BSAI	Ry_ayu	1			1.168999
BSAI	Ry_ay	1			1.168663
BSAI	R_ayg	3			1.168233
BSAI	Rp_ayg	3			1.167306
BSAI	Rb_ayu	14			1.166661
BSAI	R_ayu	14			1.164365
BSAI	Rp_ayu	14			1.164296
BSAI	Rb_ay	14			1.157740
BSAI	Ro_ayg	15			1.157037
BSAI	R_ay	14			1.154927
BSAI	Rp_ay	14			1.154906
BSAI	Ry_ayg	2			1.151586
BSAI	Hy_ay	14			1.150162
BSAI	Hy_ayu	14			1.148326
BSAI	Ry_ayu	43			1.146166
BSAI	Ry_ay	43			1.145972
BSAI	Ro_ayg	16			1.143174
BSAI	Ro_ayg	18			1.139277
BSAI	R_ayu	7			1.134410
BSAI	Rp_ayu	7			1.134317
BSAI	Rb_ay	6			1.133369
BSAI	Rb_ayu	6			1.133185
BSAI	Rb_ayu	7			1.133013
BSAI	Ro_ayg	10			1.132184
BSAI	Rb_ayu	22			1.129505
BSAI	Rp_ay	7			1.129472
BSAI	R_ay	7			1.129454
BSAI	Rb_ay	22			1.128597
BSAI	R_ayu	22			1.128314
BSAI	Rb_ay	7			1.128070
BSAI	Rp_ayu	22			1.127839
BSAI	R_ay	22			1.127394
BSAI	Rp_ay	22			1.126935
BSAI	Rp_ayg	14			1.126773
BSAI	Ho_ayu	5			1.126604
BSAI	Ho_ay	5			1.125901
BSAI	R_ayg	14			1.125868
BSAI	Ry_ayu	17			1.122597
BSAI	Ry_ay	17			1.122488
BSAI	Hb_ayu	3			1.121771
BSAI	Rp_ayg	17			1.121419
BSAI	R_ayg	17			1.121253
BSAI	Hp_ayu	3			1.118380
BSAI	Ho_ayg	16			1.112493
BSAI	Rp_ay	6			1.111920
BSAI	R_ay	6			1.111919
BSAI	R_ayu	6			1.111750
BSAI	Rp_ayu	6			1.111749
BSAI	Ro_ayg	20			1.110674
CI	Ro_ayu	9			1.282099
CI	Ro_ayu	6			1.268526
CI	Ro_ay	6			1.263341
CI	Ro_ay	9			1.263310
CI	Ro_ayg	6			1.238822
CI	Ro_ayg	3			1.236805
CI	Ro_ayg	2			1.231420
CI	Ro_ayu	7			1.221428
CI	Ro_ay	2			1.219775
CI	Ro_ayu	12			1.177882
CI	Ro_ay	11			1.177067
CI	Ro_ayu	11			1.159453
CI	Ro_ay	7			1.152899
CI	Ro_ayg	11			1.152133
CI	R_ayu	9			1.151718
CI	Ro_ay	3			1.144441
CI	Ro_ayu	3			1.143487
CI	Ry_ayu	27			1.142699
CI	Ro_ayu	1			1.138566
CI	Ro_ayu	5			1.137737
CI	Ro_ayg	4			1.137657
CI	Ro_ay	8			1.127594
CI	Ro_ayg	8			1.126915
CI	Ro_ayg	9			1.126878
CI	R_ay	9			1.125229
CI	Ro_ay	5			1.117120
CI	R_ay	6			1.112708
CSEO	beta2_pH			3	1.245228
CSEO	tau_prigui_pre				1.234126
EWYKT	beta2_pH			3	1.305318
EWYKT	tau_prigui_pre				1.289403
EWYKT	Rd_ayu	47			1.253142
EWYKT	Rd_ay	47			1.253142
EWYKT	Bdnye_ayu	47			1.252274
EWYKT	Bdnye_ay	47			1.252274
EWYKT	Tdnye_ayu	47			1.252150
EWYKT	Tdnye_ay	47			1.252150
EWYKT	Rdnye_ayu	47			1.252149
EWYKT	Rdnye_ay	47			1.252149
EWYKT	R_ay	47			1.250901
EWYKT	R_ayu	47			1.250901
EWYKT	Ro_ay	47			1.249834
EWYKT	Ro_ayu	47			1.249834
EWYKT	Rdnye_ayu	45			1.240141
EWYKT	Ro_ayu	45			1.239185
EWYKT	Ro_ay	45			1.238740
EWYKT	Rdnye_ay	45			1.235550
EWYKT	Tdnye_ayu	45			1.229499
EWYKT	Ts_ay	47			1.229336
EWYKT	Rs_ay	47			1.229336
EWYKT	Ts_ayu	47			1.229336
EWYKT	Rs_ayu	47			1.229336
EWYKT	Bdnye_ayu	45			1.229138
EWYKT	Rs_ayu	45			1.223911
EWYKT	Tdnye_ay	45			1.219520
EWYKT	Bdnye_ay	45			1.215941
EWYKT	Ts_ayu	45			1.208483
EWYKT	Rs_ayu	44			1.185888
EWYKT	Rs_ayu	25			1.185319
EWYKT	Rs_ayu	17			1.184279
EWYKT	Ry_ayu	45			1.183545
EWYKT	Ry_ay	45			1.183545
EWYKT	Ts_ayg	3			1.164933
EWYKT	Hs_ayg	3			1.163523
EWYKT	Ts_ay	3			1.162776
EWYKT	Hs_ay	3			1.161483
EWYKT	Rs_ayu	35			1.159555
EWYKT	Rs_ayu	8			1.147612
EWYKT	Ro_ayu	44			1.146592
EWYKT	p_dsr	46	2		1.146274
EWYKT	Ro_ay	44			1.144391
EWYKT	Rd_ayu	45			1.140338
EWYKT	Rd_ay	45			1.140186
EWYKT	Rdnye_ayu	44			1.132226
EWYKT	R_ay	45			1.129611
EWYKT	R_ayu	45			1.129583
EWYKT	Ro_ayu	46			1.126192
EWYKT	Ro_ay	46			1.126151
EWYKT	Rdnye_ay	46			1.125092
EWYKT	Rdnye_ayu	46			1.125090
EWYKT	Tdnye_ayu	46			1.124505
EWYKT	Tdnye_ay	46			1.124480
EWYKT	Bdnye_ayu	46			1.123171
EWYKT	Bdnye_ay	46			1.123049
EWYKT	Rs_ayg	3			1.121302
EWYKT	Rs_ay	3			1.116553
EWYKT	Ts_ayu	44			1.115502
EWYKT	Rs_ayu	46			1.115155
EWYKT	Ts_ayu	46			1.114612
EWYKT	Rs_ay	46			1.111992
NG	tau_prigui_pre				1.282439
NSEI	Ry_ayu	46			1.287358
NSEI	Ry_ay	46			1.287357
NSEI	Rd_ayu	46			1.284948
NSEI	Rd_ay	46			1.284948
NSEI	R_ayu	46			1.270969
NSEI	R_ay	46			1.270968
NSEI	beta2_pH			3	1.253126
NSEI	beta2_black				1.122424
NSEO	tau_prigui_pre				1.291294
NSEO	R_ay	46			1.254301
NSEO	R_ayu	46			1.254300
NSEO	Ry_ay	46			1.254268
NSEO	Ry_ayu	46			1.254268
NSEO	Rd_ay	46			1.254267
NSEO	Rd_ayu	46			1.254267
NSEO	beta2_pH			3	1.251974
NSEO	R_ayu	47			1.166949
NSEO	R_ay	47			1.166945
NSEO	Ry_ayu	47			1.166765
NSEO	Rd_ayu	47			1.166765
NSEO	Rd_ay	47			1.166758
NSEO	Ry_ay	47			1.166758
NSEO	Ry_ayu	44			1.164586
NSEO	Rd_ayu	44			1.164271
NSEO	Ry_ay	44			1.164126
NSEO	Rd_ay	44			1.163759
NSEO	Rs_ayg	7			1.126126
PWSI	tau_prigui_pre				1.279677
PWSI	mu_beta2_pH			3	1.234868
PWSO	tau_prigui_pre				1.275588
PWSO	Ro_ayg	14			1.240188
PWSO	Ro_ayu	4			1.140729
PWSO	Ro_ayg	3			1.124138
PWSO	Ro_ay	4			1.111176
SOKO2SAP	Rb_ayu	22			1.289751
SOKO2SAP	Rb_ay	22			1.289751
SOKO2SAP	R_ayu	22			1.289727
SOKO2SAP	R_ay	22			1.289727
SOKO2SAP	Rp_ayu	22			1.289727
SOKO2SAP	Rp_ay	22			1.289726
SOKO2SAP	Rb_ayu	8			1.289005
SOKO2SAP	Rb_ay	8			1.289005
SOKO2SAP	Rp_ayu	8			1.288995
SOKO2SAP	R_ayu	8			1.288995
SOKO2SAP	Rp_ay	8			1.288995
SOKO2SAP	R_ay	8			1.288995
SOKO2SAP	R_ayu	10			1.277900
SOKO2SAP	Rp_ayu	10			1.277900
SOKO2SAP	R_ay	10			1.277900
SOKO2SAP	Rp_ay	10			1.277900
SOKO2SAP	Rb_ayu	10			1.277889
SOKO2SAP	Rb_ay	10			1.277889
SOKO2SAP	Rb_ayu	5			1.272014
SOKO2SAP	Rb_ay	5			1.272014
SOKO2SAP	R_ayu	5			1.271843
SOKO2SAP	Rp_ayu	5			1.271843
SOKO2SAP	R_ay	5			1.271843
SOKO2SAP	Rp_ay	5			1.271843
SOKO2SAP	Ro_ayu	16			1.263837
SOKO2SAP	R_ay	7			1.258174
SOKO2SAP	Rp_ay	7			1.258174
SOKO2SAP	Rp_ayu	7			1.258174
SOKO2SAP	R_ayu	7			1.258174
SOKO2SAP	Rb_ay	7			1.257537
SOKO2SAP	Rb_ayu	7			1.257537
SOKO2SAP	Rb_ayu	15			1.256514
SOKO2SAP	Rb_ay	15			1.256513
SOKO2SAP	R_ayu	15			1.255616
SOKO2SAP	Rp_ayu	15			1.255616
SOKO2SAP	R_ay	15			1.255615
SOKO2SAP	Rp_ay	15			1.255615
SOKO2SAP	Ro_ay	16			1.249214
SOKO2SAP	R_ayu	16			1.243872
SOKO2SAP	Rp_ayu	16			1.243872
SOKO2SAP	R_ay	16			1.243871
SOKO2SAP	Rp_ay	16			1.243870
SOKO2SAP	Rb_ayu	16			1.241871
SOKO2SAP	Rb_ay	16			1.241870
SOKO2SAP	Ry_ayu	6			1.241682
SOKO2SAP	Ry_ay	6			1.241417
SOKO2SAP	R_ayu	9			1.236708
SOKO2SAP	Rp_ayu	9			1.236708
SOKO2SAP	R_ay	9			1.236708
SOKO2SAP	Rp_ay	9			1.236708
SOKO2SAP	Rb_ayu	9			1.235285
SOKO2SAP	Rb_ay	9			1.235284
SOKO2SAP	tau_prigui_pre				1.195651
SOKO2SAP	Rb_ay	6			1.191622
SOKO2SAP	Rb_ayu	6			1.191621
SOKO2SAP	R_ay	6			1.190759
SOKO2SAP	Rp_ay	6			1.190759
SOKO2SAP	R_ayu	6			1.190759
SOKO2SAP	Rp_ayu	6			1.190759
SOKO2SAP	Rb_ayu	21			1.175557
SOKO2SAP	Rb_ay	21			1.175513
SOKO2SAP	R_ayu	21			1.173831
SOKO2SAP	Rp_ayu	21			1.173824
SOKO2SAP	R_ay	21			1.173782
SOKO2SAP	Rp_ay	21			1.173776
SOKO2SAP	Rb_ayu	19			1.165934
SOKO2SAP	Rb_ay	19			1.165920
SOKO2SAP	Ry_ayu	32			1.165197
SOKO2SAP	Ry_ay	32			1.165181
SOKO2SAP	R_ayu	19			1.164900
SOKO2SAP	Rp_ayu	19			1.164898
SOKO2SAP	R_ay	19			1.164886
SOKO2SAP	Rp_ay	19			1.164884
SOKO2SAP	Rb_ayu	2			1.157130
SOKO2SAP	Rb_ay	2			1.157129
SOKO2SAP	R_ayu	2			1.149254
SOKO2SAP	Rp_ayu	2			1.149254
SOKO2SAP	R_ay	2			1.149254
SOKO2SAP	Rp_ay	2			1.149254
SOKO2SAP	Ry_ayu	10			1.144131
SOKO2SAP	Ry_ay	10			1.143941
SOKO2SAP	Rb_ayu	24			1.143664
SOKO2SAP	Rb_ay	24			1.143663
SOKO2SAP	R_ayu	24			1.142439
SOKO2SAP	R_ay	24			1.142439
SOKO2SAP	Rp_ayu	24			1.142422
SOKO2SAP	Rp_ay	24			1.142422
SOKO2SAP	Rb_ay	4			1.140415
SOKO2SAP	Rb_ayu	4			1.140415
SOKO2SAP	R_ay	4			1.140405
SOKO2SAP	Rp_ay	4			1.140405
SOKO2SAP	Rp_ayu	4			1.140405
SOKO2SAP	R_ayu	4			1.140405
SOKO2SAP	R_ayu	3			1.135039
SOKO2SAP	Rp_ayu	3			1.135039
SOKO2SAP	R_ay	3			1.135038
SOKO2SAP	Rp_ay	3			1.135038
SOKO2SAP	Rb_ayu	3			1.132635
SOKO2SAP	Rb_ay	3			1.132634
SOKO2SAP	Ry_ayu	40			1.128683
SOKO2SAP	Ry_ay	40			1.128657
SOKO2SAP	Ry_ayu	9			1.126843
SOKO2SAP	Ry_ay	9			1.126379
SOKO2SAP	Ry_ayu	17			1.121549
SOKO2SAP	Ry_ay	17			1.121456
SOKO2SAP	R_ayu	17			1.121030
SOKO2SAP	Rp_ayu	17			1.121030
SOKO2SAP	R_ay	17			1.121028
SOKO2SAP	Rp_ay	17			1.121028
SOKO2SAP	Rb_ayu	17			1.120900
SOKO2SAP	Rb_ay	17			1.120898
SOKO2SAP	Ry_ayu	43			1.119531
SOKO2SAP	Ry_ay	43			1.119501
SOKO2SAP	Rb_ay	12			1.117876
SOKO2SAP	Rb_ayu	12			1.117876
SOKO2SAP	Ro_ayu	19			1.116901
SOKO2SAP	Rb_ayu	14			1.116828
SOKO2SAP	Rb_ay	14			1.116828
SOKO2SAP	R_ayu	14			1.116151
SOKO2SAP	Rp_ayu	14			1.116151
SOKO2SAP	R_ay	14			1.116151
SOKO2SAP	Rp_ay	14			1.116151
SOKO2SAP	R_ayu	11			1.110362
SOKO2SAP	Rp_ayu	11			1.110362
SOKO2SAP	Rp_ay	11			1.110356
SOKO2SAP	R_ay	11			1.110356
SSEI	beta2_pH			3	1.232050
SSEI	tau_prigui_pre				1.173427
SSEI	Ry_ayg	8			1.151944
SSEO	tau_prigui_pre				1.287649
SSEO	beta2_pH			3	1.243600
SSEO	Ry_ayu	46			1.217763
SSEO	Ry_ay	46			1.217763
SSEO	Rd_ayu	46			1.217750
SSEO	Rd_ay	46			1.217749
SSEO	R_ayu	46			1.217746
SSEO	R_ay	46			1.217745
SSEO	Rs_ayg	10			1.150116
SSEO	Ry_ayu	47			1.146459
SSEO	Ry_ay	47			1.146459
SSEO	Rd_ayu	47			1.146422
SSEO	Rd_ay	47			1.146422
SSEO	R_ayu	47			1.146381
SSEO	R_ay	47			1.146381
SSEO	Rs_ay	10			1.127920
SSEO	Rs_ayu	7			1.123103
WKMA	tau_prigui_pre				1.245081
WKMA	Ry_ayu	16			1.132407
WKMA	Ry_ayu	15			1.127051
afognak	tau_prigui_pre				1.281846
afognak	Rp_ayu	2			1.212559
afognak	Rb_ayu	2			1.207299
afognak	Ry_ayu	13			1.206822
afognak	R_ayu	2			1.204849
afognak	Ro_ayg	16			1.197903
afognak	Ry_ay	13			1.178703
afognak	Ho_ayg	16			1.172262
afognak	Ry_ayg	2			1.161520
afognak	Ho_ay	16			1.158672
afognak	Ro_ay	16			1.154185
afognak	Rp_ayu	8			1.134733
afognak	Rb_ayu	8			1.134228
afognak	R_ayu	8			1.129586
afognak	beta2_pH			1	1.124277
afognak	Ry_ay	12			1.114117
afognak	Ry_ayg	10			1.113987
eastside	Rb_ay	3			1.291083
eastside	Rp_ay	3			1.291079
eastside	Rp_ayu	3			1.291073
eastside	Rb_ayu	3			1.291073
eastside	Ro_ayu	4			1.281702
eastside	Rp_ayu	5			1.281695
eastside	Ro_ay	4			1.281530
eastside	R_ayu	4			1.281485
eastside	R_ay	4			1.281024
eastside	Rb_ayu	5			1.280755
eastside	Rp_ayu	9			1.273468
eastside	Rb_ayu	9			1.273354
eastside	Rb_ayu	2			1.271388
eastside	Rp_ayu	2			1.271127
eastside	Ro_ayu	6			1.269837
eastside	Ro_ay	6			1.269820
eastside	R_ayu	6			1.269752
eastside	R_ay	6			1.269715
eastside	Rp_ayu	4			1.264951
eastside	Rb_ayu	4			1.264484
eastside	Rp_ayu	14			1.261562
eastside	R_ay	3			1.261521
eastside	Rp_ay	5			1.261391
eastside	Rb_ayu	15			1.261311
eastside	R_ayu	3			1.261244
eastside	Ro_ayu	12			1.260884
eastside	Ro_ay	12			1.260351
eastside	R_ayu	12			1.260238
eastside	Rb_ay	5			1.259951
eastside	Rp_ayu	15			1.259729
eastside	Rb_ayu	14			1.259580
eastside	R_ay	12			1.259179
eastside	Ry_ayu	18			1.255743
eastside	R_ayu	5			1.254487
eastside	Ro_ayu	5			1.254137
eastside	R_ay	5			1.253989
eastside	Ro_ay	5			1.253790
eastside	Rp_ayu	12			1.251496
eastside	Ro_ayu	21			1.251424
eastside	R_ayu	21			1.251172
eastside	Ro_ay	21			1.250692
eastside	R_ay	21			1.248630
eastside	Rb_ayu	12			1.245817
eastside	Rb_ayu	6			1.239875
eastside	Rb_ayu	10			1.239271
eastside	Rp_ayu	6			1.238910
eastside	Rp_ayu	10			1.238708
eastside	Rb_ay	2			1.234981
eastside	Rp_ay	2			1.234594
eastside	Rp_ay	4			1.230503
eastside	Rb_ay	4			1.230367
eastside	Ho_ayu	27			1.229738
eastside	Ro_ayu	7			1.226185
eastside	R_ayu	7			1.225129
eastside	Ro_ay	7			1.224996
eastside	Rb_ayu	13			1.221863
eastside	Rp_ayu	13			1.221274
eastside	R_ay	7			1.221229
eastside	Rb_ayu	8			1.219804
eastside	Rb_ay	9			1.218054
eastside	Rp_ayu	8			1.216476
eastside	Rp_ay	9			1.214682
eastside	Ro_ayu	20			1.213116
eastside	Ry_ayu	2			1.212856
eastside	Ro_ay	20			1.209251
eastside	R_ayu	20			1.209057
eastside	Ry_ayu	3			1.207155
eastside	Rb_ay	14			1.206455
eastside	Rp_ay	14			1.206250
eastside	Ro_ayu	14			1.202764
eastside	Ro_ay	14			1.200868
eastside	R_ay	20			1.199703
eastside	Rp_ay	12			1.199689
eastside	Rb_ay	12			1.195862
eastside	Rb_ay	15			1.193648
eastside	Hy_ayu	46			1.188795
eastside	Rp_ay	15			1.187093
eastside	Rb_ay	10			1.186970
eastside	Rp_ayu	16			1.184772
eastside	Rb_ayu	16			1.184129
eastside	Rp_ay	10			1.182056
eastside	Rb_ay	6			1.180024
eastside	Rp_ay	6			1.179044
eastside	Rp_ayu	11			1.179023
eastside	Rb_ayu	11			1.177821
eastside	R_ayu	14			1.176679
eastside	Ry_ayu	13			1.175808
eastside	Ry_ayu	20			1.175774
eastside	Ro_ayu	3			1.170715
eastside	Ro_ay	3			1.169731
eastside	R_ay	14			1.168105
eastside	Ry_ayu	1			1.168084
eastside	Rp_ayg	2			1.157676
eastside	Ro_ayg	1			1.156115
eastside	Rb_ay	13			1.154095
eastside	Rb_ayg	2			1.152739
eastside	Rb_ayu	7			1.152143
eastside	Ro_ayu	23			1.151735
eastside	Rp_ayu	7			1.151640
eastside	Rp_ayu	18			1.151335
eastside	Ro_ay	23			1.151208
eastside	Ro_ayu	18			1.148995
eastside	R_ayu	18			1.148275
eastside	Rp_ay	13			1.148156
eastside	Ho_ayu	13			1.148114
eastside	Ro_ay	18			1.147218
eastside	R_ayu	23			1.146614
eastside	Rb_ayg	1			1.146258
eastside	R_ay	23			1.146183
eastside	R_ay	18			1.144140
eastside	Rb_ayu	18			1.142294
eastside	Rb_ay	7			1.140417
eastside	Rp_ay	7			1.140259
eastside	Rp_ayg	1			1.139988
eastside	Ry_ayu	47			1.136489
eastside	Ry_ayu	12			1.136356
eastside	Ho_ayu	35			1.135563
eastside	R_ayg	2			1.134869
eastside	Ro_ayg	7			1.134494
eastside	R_ayg	1			1.133377
eastside	Ho_ayu	46			1.133364
eastside	Rp_ayg	6			1.128357
eastside	Rb_ay	8			1.126376
eastside	tau_prigui_pre				1.124245
eastside	Rb_ayg	6			1.122087
eastside	Ro_ay	1			1.121713
eastside	Ro_ayu	1			1.121582
eastside	R_ay	1			1.121504
eastside	R_ayu	1			1.121416
eastside	Rp_ay	8			1.121217
eastside	Ry_ayu	30			1.120598
eastside	Ry_ayu	4			1.119340
eastside	Ry_ayu	27			1.117467
eastside	Rp_ayg	3			1.111136
eastside	Ro_ay	9			1.110654
eastside	Rb_ayg	3			1.110076
northeast	Ro_ay	1			1.290381
northeast	Ro_ayg	1			1.290332
northeast	Ro_ayu	1			1.289697
northeast	R_ayg	1			1.285237
northeast	R_ay	1			1.284964
northeast	Ro_ayu	6			1.282808
northeast	Ro_ay	6			1.276532
northeast	R_ayu	1			1.275240
northeast	Ro_ayg	6			1.258392
northeast	Ro_ayg	2			1.246486
northeast	Ro_ayg	3			1.235095
northeast	Ro_ay	3			1.232086
northeast	Ro_ayu	3			1.231020
northeast	Ro_ay	2			1.230450
northeast	R_ayu	6			1.214916
northeast	R_ay	6			1.168729
northeast	Ro_ayu	8			1.166295
northeast	Ro_ayu	9			1.151524
northeast	tau_prigui_pre				1.137693
northeast	Ro_ayu	10			1.137241
northeast	Ro_ayu	19			1.126518
northeast	Ro_ay	8			1.125546
northeast	Ro_ayu	7			1.116076
northeast	R_ayg	2			1.112811
northeast	Ro_ayu	15			1.112400
northeast	R_ayg	3			1.111635

Parameter estimates:

Summary Table of Parameter Estimates

Parameter	mean	sd	Lower_CI	Median	Upper_CI
mu_bc_H[1]	-0.151	0.071	-0.279	-0.153	-0.006
mu_bc_H[2]	-0.110	0.043	-0.185	-0.112	-0.018
mu_bc_H[3]	-0.447	0.072	-0.585	-0.449	-0.304
mu_bc_H[4]	-1.181	0.236	-1.679	-1.172	-0.738
mu_bc_H[5]	0.823	0.969	-0.330	0.624	3.309
mu_bc_H[6]	-2.156	0.340	-2.821	-2.160	-1.484
mu_bc_H[7]	-0.489	0.113	-0.729	-0.484	-0.282
mu_bc_H[8]	0.279	0.364	-0.320	0.241	1.069
mu_bc_H[9]	-0.369	0.151	-0.660	-0.371	-0.067
mu_bc_H[10]	-0.134	0.066	-0.256	-0.136	0.004
mu_bc_H[11]	-0.122	0.038	-0.196	-0.122	-0.044
mu_bc_H[12]	-0.265	0.107	-0.496	-0.257	-0.065
mu_bc_H[13]	-0.164	0.081	-0.314	-0.166	0.000
mu_bc_H[14]	-0.345	0.110	-0.573	-0.344	-0.140
mu_bc_H[15]	-0.344	0.050	-0.441	-0.345	-0.243
mu_bc_H[16]	-0.238	0.388	-0.944	-0.250	0.604
mu_bc_R[1]	0.563	31.202	-61.729	0.509	61.066
mu_bc_R[2]	0.087	31.512	-63.730	-0.176	63.683
mu_bc_R[3]	-0.329	31.264	-62.155	-0.820	62.285
mu_bc_R[4]	0.971	32.020	-61.647	0.770	61.298
mu_bc_R[5]	0.016	32.029	-65.682	0.455	63.296
mu_bc_R[6]	0.236	31.594	-62.401	-0.093	60.844
mu_bc_R[7]	0.626	31.368	-61.254	0.010	61.046
mu_bc_R[8]	-0.700	32.355	-64.278	-0.643	62.592
mu_bc_R[9]	0.781	31.854	-63.204	0.915	62.579
mu_bc_R[10]	0.665	31.158	-59.878	-0.115	61.143
mu_bc_R[11]	-0.324	31.885	-62.701	-0.468	62.020
mu_bc_R[12]	-0.368	31.861	-61.788	-0.833	62.790
mu_bc_R[13]	0.245	32.313	-62.635	0.195	62.330
mu_bc_R[14]	-0.537	31.298	-62.292	-0.512	61.654
mu_bc_R[15]	1.225	31.863	-61.168	1.965	64.235
mu_bc_R[16]	-0.514	31.864	-62.134	-0.884	62.361
tau_pH[1]	6.344	0.544	5.314	6.328	7.474
tau_pH[2]	1.799	0.208	1.414	1.793	2.234
tau_pH[3]	2.081	0.236	1.642	2.066	2.557
beta0_pH[1,1]	0.208	0.286	-0.473	0.247	0.643
beta0_pH[2,1]	0.581	0.518	-0.594	0.706	1.314
beta0_pH[3,1]	0.776	0.634	-0.706	0.922	1.591
beta0_pH[4,1]	0.852	0.600	-0.584	0.990	1.645
beta0_pH[5,1]	-1.263	0.474	-2.492	-1.159	-0.673
beta0_pH[6,1]	-0.867	0.478	-2.059	-0.778	-0.177
beta0_pH[7,1]	0.748	0.089	0.575	0.747	0.923
beta0_pH[8,1]	-0.735	0.408	-1.677	-0.659	-0.193
beta0_pH[9,1]	-1.354	0.574	-2.807	-1.265	-0.521
beta0_pH[10,1]	-0.203	0.328	-1.000	-0.146	0.280
beta0_pH[11,1]	-0.130	0.183	-0.511	-0.121	0.214
beta0_pH[12,1]	0.404	0.181	0.033	0.408	0.742
beta0_pH[13,1]	-0.191	0.153	-0.507	-0.184	0.090
beta0_pH[14,1]	-0.395	0.159	-0.724	-0.388	-0.096
beta0_pH[15,1]	-0.119	0.181	-0.503	-0.108	0.209
beta0_pH[16,1]	-0.240	0.179	-0.622	-0.224	0.080
beta0_pH[1,2]	2.609	0.222	2.161	2.607	3.036
beta0_pH[2,2]	2.864	0.173	2.521	2.865	3.204
beta0_pH[3,2]	3.363	0.194	2.999	3.358	3.744
beta0_pH[4,2]	3.061	0.166	2.739	3.059	3.387
beta0_pH[5,2]	4.523	1.372	2.707	4.243	8.088
beta0_pH[6,2]	3.288	0.250	2.807	3.288	3.788
beta0_pH[7,2]	1.930	0.238	1.462	1.941	2.381
beta0_pH[8,2]	2.830	0.211	2.422	2.828	3.235
beta0_pH[9,2]	3.903	0.285	3.340	3.897	4.486
beta0_pH[10,2]	3.807	0.237	3.356	3.800	4.286
beta0_pH[11,2]	1.868	0.167	1.547	1.865	2.199
beta0_pH[12,2]	1.629	0.203	1.232	1.624	2.027
beta0_pH[13,2]	2.344	0.205	1.949	2.341	2.745
beta0_pH[14,2]	1.640	0.182	1.271	1.641	2.002
beta0_pH[15,2]	2.414	0.199	2.031	2.412	2.800
beta0_pH[16,2]	2.522	0.207	2.116	2.519	2.934
beta0_pH[1,3]	0.253	0.874	-2.030	0.424	1.297
beta0_pH[2,3]	2.079	0.187	1.702	2.081	2.441
beta0_pH[3,3]	2.623	0.171	2.287	2.622	2.960
beta0_pH[4,3]	3.000	0.184	2.651	3.000	3.371
beta0_pH[5,3]	3.333	1.829	0.962	2.923	7.890
beta0_pH[6,3]	1.214	0.394	0.493	1.191	2.036
beta0_pH[7,3]	0.560	0.205	0.175	0.552	0.980
beta0_pH[8,3]	0.268	0.197	-0.125	0.267	0.645
beta0_pH[9,3]	-2.382	1.118	-4.456	-2.450	-0.320
beta0_pH[10,3]	-0.763	0.924	-2.857	-0.678	0.740
beta0_pH[11,3]	1.032	0.398	0.187	1.050	1.784
beta0_pH[12,3]	0.786	0.448	-0.163	0.809	1.567
beta0_pH[13,3]	0.990	0.441	0.065	1.038	1.672
beta0_pH[14,3]	0.644	0.455	-0.394	0.686	1.427
beta0_pH[15,3]	0.822	0.405	-0.032	0.881	1.425
beta0_pH[16,3]	0.958	0.403	0.072	1.025	1.550
beta1_pH[1,1]	4.067	1.049	2.749	3.787	6.838
beta1_pH[2,1]	2.876	0.807	1.826	2.662	4.799
beta1_pH[3,1]	3.002	1.209	1.556	2.708	5.968
beta1_pH[4,1]	3.268	1.138	1.925	2.976	6.483
beta1_pH[5,1]	2.684	0.530	1.982	2.580	4.094
beta1_pH[6,1]	3.102	0.849	1.784	2.963	5.127
beta1_pH[7,1]	0.000	0.000	0.000	0.000	0.000
beta1_pH[8,1]	3.135	0.763	1.980	3.028	4.949
beta1_pH[9,1]	3.021	0.705	2.029	2.896	4.823
beta1_pH[10,1]	2.826	0.473	2.121	2.739	3.968
beta1_pH[11,1]	3.370	0.234	2.943	3.355	3.868
beta1_pH[12,1]	3.003	0.210	2.594	3.001	3.421
beta1_pH[13,1]	2.900	0.217	2.486	2.898	3.321
beta1_pH[14,1]	3.498	0.222	3.072	3.494	3.965
beta1_pH[15,1]	2.723	0.234	2.289	2.708	3.223
beta1_pH[16,1]	3.051	0.224	2.654	3.038	3.531
beta1_pH[1,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[2,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[3,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[4,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[5,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[6,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[7,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[8,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[9,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[10,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[11,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[12,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[13,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[14,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[15,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[16,2]	0.000	0.000	0.000	0.000	0.000
beta1_pH[1,3]	3.189	1.861	1.200	2.612	7.838
beta1_pH[2,3]	0.000	0.000	0.000	0.000	0.000
beta1_pH[3,3]	0.000	0.000	0.000	0.000	0.000
beta1_pH[4,3]	0.000	0.000	0.000	0.000	0.000
beta1_pH[5,3]	0.000	0.000	0.000	0.000	0.000
beta1_pH[6,3]	0.000	0.000	0.000	0.000	0.000
beta1_pH[7,3]	0.000	0.000	0.000	0.000	0.000
beta1_pH[8,3]	3.612	0.735	2.213	3.596	5.117
beta1_pH[9,3]	4.681	1.327	2.400	4.674	7.402
beta1_pH[10,3]	6.158	2.478	2.741	5.658	12.197
beta1_pH[11,3]	1.625	0.460	0.729	1.617	2.552
beta1_pH[12,3]	2.506	0.506	1.584	2.482	3.559
beta1_pH[13,3]	0.581	0.483	0.000	0.545	1.591
beta1_pH[14,3]	1.596	0.522	0.612	1.563	2.731
beta1_pH[15,3]	0.488	0.442	0.000	0.402	1.440
beta1_pH[16,3]	0.471	0.438	0.000	0.388	1.477
beta2_pH[1,1]	0.343	0.119	0.159	0.326	0.610
beta2_pH[2,1]	0.418	0.264	0.128	0.355	1.094
beta2_pH[3,1]	0.372	0.367	0.085	0.253	1.303
beta2_pH[4,1]	0.311	0.187	0.093	0.265	0.775
beta2_pH[5,1]	1.553	1.044	0.298	1.402	4.075
beta2_pH[6,1]	0.234	0.164	0.103	0.203	0.522
beta2_pH[7,1]	0.000	0.000	0.000	0.000	0.000
beta2_pH[8,1]	0.253	0.163	0.113	0.232	0.513
beta2_pH[9,1]	0.351	0.148	0.157	0.328	0.694
beta2_pH[10,1]	0.507	0.236	0.214	0.463	1.089
beta2_pH[11,1]	0.764	0.175	0.484	0.744	1.158
beta2_pH[12,1]	1.128	0.324	0.699	1.066	1.892
beta2_pH[13,1]	0.794	0.193	0.479	0.775	1.220
beta2_pH[14,1]	0.810	0.169	0.537	0.792	1.201
beta2_pH[15,1]	0.736	0.213	0.395	0.714	1.218
beta2_pH[16,1]	0.798	0.205	0.467	0.776	1.256
beta2_pH[1,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[2,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[3,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[4,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[5,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[6,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[7,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[8,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[9,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[10,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[11,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[12,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[13,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[14,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[15,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[16,2]	0.000	0.000	0.000	0.000	0.000
beta2_pH[1,3]	3.992	5.873	0.107	0.676	20.072
beta2_pH[2,3]	0.000	0.000	0.000	0.000	0.000
beta2_pH[3,3]	0.000	0.000	0.000	0.000	0.000
beta2_pH[4,3]	0.000	0.000	0.000	0.000	0.000
beta2_pH[5,3]	0.000	0.000	0.000	0.000	0.000
beta2_pH[6,3]	0.000	0.000	0.000	0.000	0.000
beta2_pH[7,3]	0.000	0.000	0.000	0.000	0.000
beta2_pH[8,3]	5.286	3.489	1.064	4.555	14.115
beta2_pH[9,3]	1.487	3.147	0.194	0.420	11.853
beta2_pH[10,3]	1.092	2.958	0.137	0.342	11.388
beta2_pH[11,3]	-7.596	6.086	-23.115	-5.621	-0.799
beta2_pH[12,3]	-7.857	6.208	-23.832	-5.613	-1.149
beta2_pH[13,3]	-7.706	6.058	-23.223	-5.926	-0.545
beta2_pH[14,3]	-7.750	6.042	-23.544	-5.637	-1.097
beta2_pH[15,3]	-7.728	6.144	-23.245	-5.888	-0.446
beta2_pH[16,3]	-7.657	6.096	-23.024	-5.840	-0.367
beta3_pH[1,1]	36.483	1.603	34.056	36.167	40.506
beta3_pH[2,1]	30.975	1.630	27.367	31.134	33.940
beta3_pH[3,1]	32.656	2.600	27.404	32.704	39.017
beta3_pH[4,1]	32.139	2.194	27.917	32.120	37.585
beta3_pH[5,1]	27.017	0.690	25.264	27.123	28.034
beta3_pH[6,1]	34.462	3.294	28.177	34.323	41.057
beta3_pH[7,1]	25.000	0.000	25.000	25.000	25.000
beta3_pH[8,1]	37.445	2.683	31.431	37.774	41.554
beta3_pH[9,1]	28.622	1.724	25.178	28.608	32.040
beta3_pH[10,1]	31.642	0.978	29.519	31.664	33.511
beta3_pH[11,1]	30.382	0.454	29.511	30.376	31.308
beta3_pH[12,1]	30.376	0.353	29.670	30.383	31.057
beta3_pH[13,1]	32.460	0.512	31.450	32.453	33.458
beta3_pH[14,1]	31.987	0.422	31.196	31.980	32.824
beta3_pH[15,1]	31.188	0.604	29.972	31.195	32.325
beta3_pH[16,1]	30.721	0.498	29.733	30.726	31.702
beta3_pH[1,2]	33.545	4.928	25.508	33.628	41.588
beta3_pH[2,2]	33.398	4.883	25.463	33.182	41.604
beta3_pH[3,2]	29.823	6.906	18.616	29.848	41.294
beta3_pH[4,2]	29.885	6.969	18.595	29.977	41.429
beta3_pH[5,2]	29.908	6.868	18.672	30.097	41.448
beta3_pH[6,2]	29.982	6.983	18.717	29.952	41.470
beta3_pH[7,2]	25.000	0.000	25.000	25.000	25.000
beta3_pH[8,2]	25.000	0.000	25.000	25.000	25.000
beta3_pH[9,2]	25.000	0.000	25.000	25.000	25.000
beta3_pH[10,2]	25.000	0.000	25.000	25.000	25.000
beta3_pH[11,2]	24.000	0.000	24.000	24.000	24.000
beta3_pH[12,2]	24.000	0.000	24.000	24.000	24.000
beta3_pH[13,2]	24.000	0.000	24.000	24.000	24.000
beta3_pH[14,2]	24.000	0.000	24.000	24.000	24.000
beta3_pH[15,2]	24.000	0.000	24.000	24.000	24.000
beta3_pH[16,2]	24.000	0.000	24.000	24.000	24.000
beta3_pH[1,3]	37.046	2.929	31.467	36.834	41.558
beta3_pH[2,3]	33.403	4.865	25.457	33.410	41.485
beta3_pH[3,3]	29.907	6.903	18.523	29.888	41.373
beta3_pH[4,3]	29.779	6.902	18.626	29.668	41.304
beta3_pH[5,3]	25.000	0.000	25.000	25.000	25.000
beta3_pH[6,3]	25.000	0.000	25.000	25.000	25.000
beta3_pH[7,3]	25.000	0.000	25.000	25.000	25.000
beta3_pH[8,3]	41.558	0.247	41.065	41.578	41.958
beta3_pH[9,3]	30.757	1.824	28.139	30.436	34.020
beta3_pH[10,3]	36.248	2.059	32.765	36.019	41.152
beta3_pH[11,3]	40.320	1.046	38.636	40.319	42.201
beta3_pH[12,3]	40.945	0.608	39.619	41.033	41.902
beta3_pH[13,3]	40.226	3.152	30.590	41.382	42.904
beta3_pH[14,3]	40.537	0.865	39.018	40.606	41.891
beta3_pH[15,3]	39.587	3.213	30.404	40.726	42.846
beta3_pH[16,3]	39.315	3.450	29.971	40.482	42.851
beta4_pH[1,1]	0.695	0.286	0.310	0.650	1.288
beta4_pH[2,1]	0.851	0.213	0.543	0.817	1.261
beta4_pH[3,1]	0.925	0.280	0.513	0.879	1.475
beta4_pH[4,1]	0.804	0.266	0.432	0.756	1.348
beta4_pH[5,1]	0.672	0.525	0.088	0.549	1.967
beta4_pH[6,1]	1.993	1.749	0.232	1.414	6.689
beta4_pH[7,1]	1.119	0.613	0.351	0.975	2.485
beta4_pH[8,1]	0.754	0.417	0.228	0.672	1.694
beta4_pH[9,1]	0.922	0.541	0.268	0.786	2.188
beta4_pH[10,1]	0.728	0.279	0.343	0.690	1.287
beta4_pH[11,1]	0.692	0.242	0.351	0.649	1.181
beta4_pH[12,1]	0.920	0.374	0.435	0.826	1.723
beta4_pH[13,1]	0.746	0.267	0.380	0.696	1.293
beta4_pH[14,1]	1.032	0.337	0.562	0.969	1.702
beta4_pH[15,1]	0.932	0.264	0.543	0.892	1.446
beta4_pH[16,1]	0.887	0.358	0.417	0.811	1.649
beta4_pH[1,2]	0.691	0.287	0.305	0.637	1.281
beta4_pH[2,2]	0.848	0.210	0.546	0.818	1.258
beta4_pH[3,2]	0.911	0.283	0.514	0.867	1.477
beta4_pH[4,2]	0.801	0.267	0.431	0.766	1.341
beta4_pH[5,2]	0.671	0.520	0.087	0.544	1.941
beta4_pH[6,2]	1.970	1.752	0.232	1.377	6.761
beta4_pH[7,2]	1.099	0.616	0.347	0.941	2.490
beta4_pH[8,2]	0.770	0.429	0.229	0.674	1.723
beta4_pH[9,2]	0.917	0.537	0.275	0.789	2.175
beta4_pH[10,2]	0.717	0.278	0.343	0.669	1.287
beta4_pH[11,2]	0.692	0.246	0.351	0.649	1.188
beta4_pH[12,2]	0.933	0.378	0.437	0.850	1.728
beta4_pH[13,2]	0.748	0.267	0.381	0.705	1.292
beta4_pH[14,2]	1.021	0.336	0.559	0.956	1.693
beta4_pH[15,2]	0.919	0.265	0.534	0.877	1.441
beta4_pH[16,2]	0.908	0.358	0.422	0.830	1.644
beta4_pH[1,3]	0.687	0.283	0.308	0.642	1.285
beta4_pH[2,3]	0.850	0.211	0.548	0.821	1.253
beta4_pH[3,3]	0.918	0.280	0.513	0.876	1.484
beta4_pH[4,3]	0.816	0.266	0.431	0.780	1.340
beta4_pH[5,3]	0.685	0.527	0.085	0.558	1.976
beta4_pH[6,3]	1.928	1.732	0.234	1.354	6.743
beta4_pH[7,3]	1.090	0.605	0.348	0.939	2.466
beta4_pH[8,3]	0.747	0.423	0.225	0.658	1.714
beta4_pH[9,3]	0.906	0.532	0.271	0.774	2.177
beta4_pH[10,3]	0.723	0.274	0.351	0.676	1.281
beta4_pH[11,3]	0.692	0.240	0.352	0.654	1.188
beta4_pH[12,3]	0.922	0.376	0.439	0.830	1.736
beta4_pH[13,3]	0.747	0.269	0.379	0.701	1.295
beta4_pH[14,3]	1.037	0.344	0.560	0.971	1.705
beta4_pH[15,3]	0.910	0.263	0.537	0.874	1.441
beta4_pH[16,3]	0.899	0.354	0.423	0.832	1.654
beta4_pH[1,4]	0.689	0.286	0.306	0.649	1.282
beta4_pH[2,4]	0.850	0.211	0.545	0.823	1.259
beta4_pH[3,4]	0.911	0.286	0.516	0.858	1.477
beta4_pH[4,4]	0.801	0.264	0.436	0.758	1.340
beta4_pH[5,4]	0.686	0.527	0.086	0.561	1.979
beta4_pH[6,4]	1.900	1.740	0.225	1.315	6.657
beta4_pH[7,4]	1.097	0.607	0.351	0.951	2.491
beta4_pH[8,4]	0.769	0.429	0.225	0.684	1.708
beta4_pH[9,4]	0.921	0.539	0.277	0.776	2.182
beta4_pH[10,4]	0.724	0.274	0.349	0.682	1.290
beta4_pH[11,4]	0.692	0.243	0.352	0.653	1.181
beta4_pH[12,4]	0.928	0.374	0.443	0.837	1.723
beta4_pH[13,4]	0.755	0.264	0.379	0.715	1.290
beta4_pH[14,4]	1.029	0.334	0.561	0.974	1.695
beta4_pH[15,4]	0.906	0.261	0.536	0.866	1.433
beta4_pH[16,4]	0.908	0.355	0.423	0.835	1.638
beta4_pH[1,5]	0.695	0.282	0.305	0.658	1.279
beta4_pH[2,5]	0.852	0.216	0.543	0.820	1.266
beta4_pH[3,5]	0.914	0.283	0.515	0.866	1.483
beta4_pH[4,5]	0.802	0.264	0.430	0.753	1.344
beta4_pH[5,5]	0.661	0.510	0.088	0.533	1.921
beta4_pH[6,5]	1.935	1.771	0.228	1.342	6.800
beta4_pH[7,5]	1.120	0.620	0.349	0.970	2.506
beta4_pH[8,5]	0.757	0.419	0.226	0.665	1.706
beta4_pH[9,5]	0.910	0.540	0.272	0.767	2.188
beta4_pH[10,5]	0.725	0.278	0.349	0.675	1.289
beta4_pH[11,5]	0.683	0.245	0.350	0.640	1.185
beta4_pH[12,5]	0.928	0.373	0.437	0.845	1.721
beta4_pH[13,5]	0.744	0.263	0.380	0.696	1.288
beta4_pH[14,5]	1.021	0.331	0.561	0.959	1.699
beta4_pH[15,5]	0.918	0.266	0.537	0.880	1.442
beta4_pH[16,5]	0.890	0.361	0.422	0.808	1.651
beta4_pH[1,6]	0.693	0.282	0.306	0.652	1.278
beta4_pH[2,6]	0.847	0.212	0.544	0.819	1.259
beta4_pH[3,6]	0.902	0.278	0.517	0.855	1.461
beta4_pH[4,6]	0.805	0.264	0.429	0.773	1.349
beta4_pH[5,6]	0.673	0.513	0.087	0.565	1.980
beta4_pH[6,6]	1.938	1.731	0.232	1.360	6.543
beta4_pH[7,6]	1.120	0.608	0.348	0.975	2.468
beta4_pH[8,6]	0.755	0.428	0.226	0.658	1.727
beta4_pH[9,6]	0.921	0.537	0.276	0.789	2.180
beta4_pH[10,6]	0.722	0.273	0.347	0.683	1.294
beta4_pH[11,6]	0.692	0.244	0.354	0.651	1.193
beta4_pH[12,6]	0.934	0.377	0.442	0.836	1.733
beta4_pH[13,6]	0.739	0.263	0.379	0.688	1.282
beta4_pH[14,6]	1.030	0.333	0.562	0.982	1.696
beta4_pH[15,6]	0.923	0.270	0.538	0.878	1.448
beta4_pH[16,6]	0.896	0.354	0.421	0.824	1.663
beta4_pH[1,7]	0.686	0.288	0.306	0.636	1.281
beta4_pH[2,7]	0.849	0.212	0.544	0.823	1.258
beta4_pH[3,7]	0.911	0.278	0.515	0.870	1.472
beta4_pH[4,7]	0.806	0.266	0.433	0.762	1.341
beta4_pH[5,7]	0.658	0.505	0.085	0.540	1.936
beta4_pH[6,7]	1.928	1.691	0.234	1.376	6.519
beta4_pH[7,7]	1.105	0.618	0.344	0.955	2.503
beta4_pH[8,7]	0.761	0.427	0.226	0.664	1.718
beta4_pH[9,7]	0.921	0.535	0.277	0.781	2.177
beta4_pH[10,7]	0.723	0.273	0.345	0.686	1.277
beta4_pH[11,7]	0.690	0.245	0.350	0.647	1.195
beta4_pH[12,7]	0.925	0.372	0.443	0.836	1.723
beta4_pH[13,7]	0.758	0.268	0.382	0.711	1.292
beta4_pH[14,7]	1.026	0.334	0.564	0.967	1.703
beta4_pH[15,7]	0.916	0.268	0.535	0.877	1.442
beta4_pH[16,7]	0.900	0.359	0.421	0.831	1.659
beta4_pH[1,8]	0.686	0.280	0.303	0.641	1.271
beta4_pH[2,8]	0.852	0.213	0.543	0.818	1.258
beta4_pH[3,8]	0.902	0.279	0.512	0.858	1.461
beta4_pH[4,8]	0.811	0.267	0.431	0.771	1.343
beta4_pH[5,8]	0.674	0.511	0.087	0.554	1.967
beta4_pH[6,8]	1.998	1.752	0.232	1.419	6.675
beta4_pH[7,8]	1.088	0.605	0.353	0.948	2.494
beta4_pH[8,8]	0.753	0.422	0.228	0.669	1.694
beta4_pH[9,8]	0.895	0.526	0.274	0.767	2.166
beta4_pH[10,8]	0.721	0.276	0.343	0.677	1.293
beta4_pH[11,8]	0.695	0.247	0.352	0.648	1.194
beta4_pH[12,8]	0.929	0.379	0.439	0.837	1.724
beta4_pH[13,8]	0.749	0.266	0.381	0.707	1.289
beta4_pH[14,8]	1.018	0.329	0.561	0.956	1.686
beta4_pH[15,8]	0.922	0.268	0.537	0.883	1.444
beta4_pH[16,8]	0.902	0.356	0.420	0.830	1.662
beta4_pH[1,9]	0.682	0.282	0.305	0.635	1.279
beta4_pH[2,9]	0.849	0.212	0.545	0.821	1.261
beta4_pH[3,9]	0.914	0.283	0.516	0.862	1.475
beta4_pH[4,9]	0.808	0.268	0.433	0.769	1.342
beta4_pH[5,9]	0.674	0.519	0.087	0.560	1.938
beta4_pH[6,9]	1.943	1.753	0.234	1.344	6.708
beta4_pH[7,9]	1.105	0.606	0.346	0.964	2.485
beta4_pH[8,9]	0.764	0.432	0.227	0.669	1.739
beta4_pH[9,9]	0.933	0.547	0.277	0.787	2.174
beta4_pH[10,9]	0.726	0.275	0.346	0.684	1.287
beta4_pH[11,9]	0.687	0.239	0.354	0.645	1.173
beta4_pH[12,9]	0.924	0.377	0.436	0.832	1.737
beta4_pH[13,9]	0.746	0.264	0.381	0.700	1.286
beta4_pH[14,9]	1.026	0.334	0.558	0.966	1.695
beta4_pH[15,9]	0.921	0.264	0.537	0.883	1.438
beta4_pH[16,9]	0.890	0.353	0.419	0.824	1.636
beta4_pH[1,10]	0.687	0.285	0.307	0.640	1.283
beta4_pH[2,10]	0.850	0.210	0.546	0.821	1.264
beta4_pH[3,10]	0.912	0.282	0.515	0.863	1.473
beta4_pH[4,10]	0.801	0.267	0.431	0.758	1.343
beta4_pH[5,10]	0.673	0.525	0.087	0.548	1.971
beta4_pH[6,10]	1.892	1.733	0.229	1.312	6.738
beta4_pH[7,10]	1.099	0.601	0.347	0.968	2.469
beta4_pH[8,10]	0.755	0.424	0.224	0.671	1.707
beta4_pH[9,10]	0.916	0.535	0.279	0.777	2.169
beta4_pH[10,10]	0.727	0.281	0.343	0.676	1.295
beta4_pH[11,10]	0.696	0.247	0.354	0.651	1.193
beta4_pH[12,10]	0.929	0.376	0.438	0.834	1.729
beta4_pH[13,10]	0.746	0.270	0.382	0.695	1.301
beta4_pH[14,10]	1.032	0.331	0.565	0.978	1.691
beta4_pH[15,10]	0.919	0.267	0.539	0.878	1.438
beta4_pH[16,10]	0.894	0.357	0.424	0.819	1.660
beta4_pH[1,11]	0.692	0.282	0.305	0.650	1.275
beta4_pH[2,11]	0.848	0.209	0.544	0.819	1.261
beta4_pH[3,11]	0.913	0.281	0.520	0.867	1.477
beta4_pH[4,11]	0.802	0.264	0.433	0.765	1.333
beta4_pH[5,11]	0.659	0.512	0.088	0.530	1.944
beta4_pH[6,11]	1.915	1.717	0.228	1.362	6.564
beta4_pH[7,11]	1.108	0.618	0.346	0.952	2.493
beta4_pH[8,11]	0.768	0.429	0.228	0.691	1.734
beta4_pH[9,11]	0.917	0.541	0.274	0.770	2.176
beta4_pH[10,11]	0.725	0.277	0.346	0.681	1.297
beta4_pH[11,11]	0.689	0.245	0.351	0.648	1.188
beta4_pH[12,11]	0.933	0.382	0.435	0.835	1.730
beta4_pH[13,11]	0.750	0.268	0.377	0.702	1.290
beta4_pH[14,11]	1.019	0.325	0.561	0.962	1.675
beta4_pH[15,11]	0.928	0.269	0.541	0.890	1.445
beta4_pH[16,11]	0.896	0.361	0.421	0.813	1.664
beta4_pH[1,12]	0.691	0.284	0.309	0.644	1.279
beta4_pH[2,12]	0.851	0.211	0.547	0.820	1.257
beta4_pH[3,12]	0.917	0.280	0.516	0.867	1.478
beta4_pH[4,12]	0.815	0.266	0.435	0.778	1.347
beta4_pH[5,12]	0.656	0.516	0.086	0.518	1.944
beta4_pH[6,12]	1.940	1.737	0.234	1.374	6.749
beta4_pH[7,12]	1.104	0.618	0.351	0.949	2.519
beta4_pH[8,12]	0.750	0.414	0.229	0.665	1.697
beta4_pH[9,12]	0.912	0.529	0.275	0.781	2.160
beta4_pH[10,12]	0.724	0.272	0.345	0.686	1.284
beta4_pH[11,12]	0.697	0.247	0.354	0.649	1.192
beta4_pH[12,12]	0.936	0.378	0.438	0.845	1.745
beta4_pH[13,12]	0.748	0.266	0.380	0.699	1.291
beta4_pH[14,12]	1.023	0.333	0.562	0.964	1.702
beta4_pH[15,12]	0.912	0.263	0.539	0.870	1.438
beta4_pH[16,12]	0.885	0.352	0.422	0.807	1.649
beta4_pH[1,13]	0.692	0.286	0.304	0.646	1.287
beta4_pH[2,13]	0.847	0.211	0.544	0.816	1.263
beta4_pH[3,13]	0.911	0.282	0.511	0.863	1.476
beta4_pH[4,13]	0.803	0.265	0.427	0.763	1.338
beta4_pH[5,13]	0.665	0.509	0.086	0.538	1.953
beta4_pH[6,13]	1.941	1.760	0.225	1.348	6.684
beta4_pH[7,13]	1.085	0.603	0.346	0.946	2.481
beta4_pH[8,13]	0.765	0.430	0.228	0.675	1.733
beta4_pH[9,13]	0.910	0.530	0.274	0.779	2.174
beta4_pH[10,13]	0.718	0.275	0.348	0.675	1.287
beta4_pH[11,13]	0.685	0.244	0.352	0.642	1.185
beta4_pH[12,13]	0.932	0.378	0.434	0.853	1.726
beta4_pH[13,13]	0.747	0.268	0.380	0.695	1.296
beta4_pH[14,13]	1.023	0.338	0.563	0.965	1.695
beta4_pH[15,13]	0.916	0.266	0.539	0.874	1.444
beta4_pH[16,13]	0.900	0.356	0.421	0.821	1.649
beta4_pH[1,14]	0.691	0.283	0.304	0.647	1.284
beta4_pH[2,14]	0.854	0.213	0.544	0.823	1.265
beta4_pH[3,14]	0.911	0.282	0.512	0.867	1.474
beta4_pH[4,14]	0.806	0.269	0.431	0.768	1.345
beta4_pH[5,14]	0.654	0.505	0.085	0.532	1.960
beta4_pH[6,14]	1.954	1.754	0.235	1.369	6.660
beta4_pH[7,14]	1.101	0.601	0.354	0.967	2.448
beta4_pH[8,14]	0.771	0.424	0.228	0.684	1.739
beta4_pH[9,14]	0.930	0.542	0.276	0.781	2.184
beta4_pH[10,14]	0.730	0.273	0.346	0.687	1.292
beta4_pH[11,14]	0.690	0.248	0.352	0.648	1.201
beta4_pH[12,14]	0.925	0.373	0.441	0.826	1.734
beta4_pH[13,14]	0.749	0.265	0.381	0.701	1.290
beta4_pH[14,14]	1.038	0.338	0.560	0.974	1.700
beta4_pH[15,14]	0.914	0.266	0.540	0.873	1.440
beta4_pH[16,14]	0.901	0.358	0.425	0.825	1.665
beta4_pH[1,15]	0.691	0.283	0.307	0.653	1.288
beta4_pH[2,15]	0.849	0.210	0.548	0.817	1.263
beta4_pH[3,15]	0.904	0.276	0.512	0.865	1.460
beta4_pH[4,15]	0.808	0.268	0.429	0.776	1.342
beta4_pH[5,15]	0.688	0.516	0.087	0.583	1.955
beta4_pH[6,15]	1.935	1.766	0.230	1.330	6.658
beta4_pH[7,15]	1.093	0.616	0.348	0.950	2.476
beta4_pH[8,15]	0.760	0.425	0.230	0.678	1.732
beta4_pH[9,15]	0.922	0.540	0.280	0.780	2.187
beta4_pH[10,15]	0.727	0.275	0.346	0.684	1.290
beta4_pH[11,15]	0.694	0.244	0.351	0.652	1.189
beta4_pH[12,15]	0.923	0.371	0.439	0.837	1.719
beta4_pH[13,15]	0.744	0.265	0.380	0.694	1.290
beta4_pH[14,15]	1.020	0.331	0.560	0.966	1.693
beta4_pH[15,15]	0.916	0.265	0.540	0.879	1.438
beta4_pH[16,15]	0.900	0.356	0.419	0.829	1.662
beta4_pH[1,16]	0.690	0.285	0.307	0.648	1.275
beta4_pH[2,16]	0.848	0.214	0.544	0.813	1.261
beta4_pH[3,16]	0.907	0.278	0.514	0.866	1.467
beta4_pH[4,16]	0.814	0.267	0.433	0.781	1.344
beta4_pH[5,16]	0.673	0.515	0.088	0.548	1.963
beta4_pH[6,16]	1.944	1.743	0.228	1.359	6.625
beta4_pH[7,16]	1.099	0.612	0.346	0.945	2.485
beta4_pH[8,16]	0.756	0.421	0.226	0.670	1.719
beta4_pH[9,16]	0.912	0.535	0.277	0.770	2.162
beta4_pH[10,16]	0.720	0.276	0.345	0.678	1.281
beta4_pH[11,16]	0.692	0.246	0.352	0.649	1.187
beta4_pH[12,16]	0.923	0.371	0.440	0.837	1.728
beta4_pH[13,16]	0.751	0.272	0.380	0.700	1.292
beta4_pH[14,16]	1.027	0.331	0.564	0.973	1.703
beta4_pH[15,16]	0.915	0.267	0.539	0.867	1.444
beta4_pH[16,16]	0.902	0.357	0.422	0.818	1.651
beta4_pH[1,17]	0.701	0.290	0.305	0.661	1.292
beta4_pH[2,17]	0.849	0.212	0.544	0.819	1.257
beta4_pH[3,17]	0.910	0.280	0.514	0.868	1.468
beta4_pH[4,17]	0.796	0.267	0.430	0.757	1.342
beta4_pH[5,17]	0.688	0.524	0.086	0.561	1.949
beta4_pH[6,17]	1.958	1.751	0.235	1.359	6.729
beta4_pH[7,17]	1.105	0.612	0.351	0.954	2.506
beta4_pH[8,17]	0.769	0.432	0.227	0.683	1.734
beta4_pH[9,17]	0.917	0.537	0.276	0.776	2.201
beta4_pH[10,17]	0.729	0.278	0.348	0.680	1.296
beta4_pH[11,17]	0.697	0.246	0.354	0.652	1.203
beta4_pH[12,17]	0.928	0.376	0.441	0.840	1.736
beta4_pH[13,17]	0.744	0.266	0.377	0.699	1.289
beta4_pH[14,17]	1.034	0.338	0.563	0.976	1.698
beta4_pH[15,17]	0.919	0.264	0.538	0.876	1.437
beta4_pH[16,17]	0.896	0.355	0.423	0.824	1.651
beta4_pH[1,18]	0.684	0.281	0.304	0.647	1.275
beta4_pH[2,18]	0.845	0.213	0.543	0.813	1.265
beta4_pH[3,18]	0.912	0.276	0.515	0.876	1.473
beta4_pH[4,18]	0.804	0.267	0.430	0.769	1.336
beta4_pH[5,18]	0.671	0.516	0.086	0.551	1.964
beta4_pH[6,18]	1.942	1.741	0.229	1.374	6.701
beta4_pH[7,18]	1.088	0.607	0.344	0.948	2.482
beta4_pH[8,18]	0.763	0.427	0.225	0.680	1.710
beta4_pH[9,18]	0.925	0.540	0.277	0.780	2.186
beta4_pH[10,18]	0.733	0.281	0.345	0.684	1.303
beta4_pH[11,18]	0.689	0.243	0.351	0.648	1.182
beta4_pH[12,18]	0.924	0.382	0.438	0.827	1.746
beta4_pH[13,18]	0.755	0.267	0.385	0.713	1.289
beta4_pH[14,18]	1.033	0.340	0.562	0.975	1.703
beta4_pH[15,18]	0.915	0.265	0.536	0.882	1.436
beta4_pH[16,18]	0.888	0.352	0.425	0.807	1.653
beta4_pH[1,19]	0.702	0.290	0.307	0.658	1.284
beta4_pH[2,19]	0.846	0.213	0.545	0.816	1.262
beta4_pH[3,19]	0.916	0.282	0.513	0.876	1.478
beta4_pH[4,19]	0.804	0.270	0.429	0.766	1.347
beta4_pH[5,19]	0.660	0.520	0.086	0.527	1.948
beta4_pH[6,19]	1.953	1.720	0.236	1.375	6.588
beta4_pH[7,19]	1.089	0.591	0.349	0.960	2.469
beta4_pH[8,19]	0.760	0.427	0.227	0.673	1.728
beta4_pH[9,19]	0.932	0.541	0.279	0.793	2.178
beta4_pH[10,19]	0.735	0.272	0.349	0.696	1.284
beta4_pH[11,19]	0.682	0.240	0.351	0.640	1.180
beta4_pH[12,19]	0.925	0.375	0.436	0.835	1.721
beta4_pH[13,19]	0.742	0.266	0.379	0.694	1.286
beta4_pH[14,19]	1.021	0.329	0.561	0.958	1.695
beta4_pH[15,19]	0.917	0.269	0.537	0.875	1.447
beta4_pH[16,19]	0.898	0.354	0.421	0.820	1.628
beta4_pH[1,20]	0.696	0.283	0.310	0.654	1.282
beta4_pH[2,20]	0.848	0.206	0.544	0.821	1.245
beta4_pH[3,20]	0.896	0.276	0.514	0.850	1.471
beta4_pH[4,20]	0.805	0.264	0.436	0.767	1.341
beta4_pH[5,20]	0.658	0.516	0.089	0.531	1.953
beta4_pH[6,20]	2.015	1.797	0.229	1.409	6.747
beta4_pH[7,20]	1.109	0.605	0.350	0.967	2.493
beta4_pH[8,20]	0.775	0.428	0.231	0.693	1.736
beta4_pH[9,20]	0.921	0.538	0.275	0.780	2.176
beta4_pH[10,20]	0.719	0.277	0.346	0.673	1.284
beta4_pH[11,20]	0.679	0.242	0.352	0.640	1.186
beta4_pH[12,20]	0.924	0.368	0.440	0.834	1.727
beta4_pH[13,20]	0.750	0.273	0.379	0.695	1.303
beta4_pH[14,20]	1.033	0.331	0.565	0.975	1.693
beta4_pH[15,20]	0.917	0.266	0.540	0.869	1.444
beta4_pH[16,20]	0.895	0.355	0.423	0.818	1.648
beta4_pH[1,21]	0.699	0.283	0.308	0.665	1.281
beta4_pH[2,21]	0.848	0.208	0.546	0.821	1.256
beta4_pH[3,21]	0.909	0.281	0.513	0.865	1.467
beta4_pH[4,21]	0.803	0.269	0.432	0.763	1.343
beta4_pH[5,21]	0.666	0.520	0.089	0.538	1.963
beta4_pH[6,21]	1.896	1.694	0.227	1.347	6.545
beta4_pH[7,21]	1.099	0.620	0.348	0.948	2.510
beta4_pH[8,21]	0.762	0.429	0.224	0.676	1.724
beta4_pH[9,21]	0.923	0.543	0.274	0.785	2.194
beta4_pH[10,21]	0.722	0.276	0.343	0.680	1.289
beta4_pH[11,21]	0.684	0.242	0.352	0.641	1.188
beta4_pH[12,21]	0.916	0.375	0.437	0.822	1.728
beta4_pH[13,21]	0.753	0.269	0.380	0.709	1.295
beta4_pH[14,21]	1.029	0.334	0.564	0.967	1.690
beta4_pH[15,21]	0.921	0.266	0.540	0.881	1.443
beta4_pH[16,21]	0.897	0.356	0.418	0.823	1.644
beta4_pH[1,22]	0.694	0.281	0.306	0.658	1.286
beta4_pH[2,22]	0.850	0.216	0.541	0.815	1.255
beta4_pH[3,22]	0.910	0.279	0.516	0.866	1.476
beta4_pH[4,22]	0.806	0.271	0.429	0.769	1.339
beta4_pH[5,22]	0.662	0.510	0.088	0.552	1.963
beta4_pH[6,22]	1.937	1.749	0.235	1.335	6.750
beta4_pH[7,22]	1.104	0.611	0.350	0.960	2.485
beta4_pH[8,22]	0.760	0.433	0.227	0.671	1.740
beta4_pH[9,22]	0.939	0.553	0.277	0.795	2.216
beta4_pH[10,22]	0.724	0.276	0.345	0.678	1.290
beta4_pH[11,22]	0.694	0.247	0.351	0.648	1.198
beta4_pH[12,22]	0.918	0.371	0.437	0.825	1.722
beta4_pH[13,22]	0.751	0.266	0.379	0.710	1.289
beta4_pH[14,22]	1.020	0.329	0.561	0.961	1.698
beta4_pH[15,22]	0.922	0.265	0.540	0.885	1.442
beta4_pH[16,22]	0.898	0.359	0.420	0.825	1.649
beta4_pH[1,23]	0.694	0.285	0.306	0.650	1.285
beta4_pH[2,23]	0.847	0.211	0.544	0.813	1.258
beta4_pH[3,23]	0.902	0.281	0.511	0.857	1.469
beta4_pH[4,23]	0.805	0.265	0.431	0.770	1.340
beta4_pH[5,23]	0.646	0.511	0.085	0.508	1.935
beta4_pH[6,23]	1.893	1.676	0.231	1.349	6.555
beta4_pH[7,23]	1.101	0.604	0.347	0.953	2.482
beta4_pH[8,23]	0.763	0.427	0.228	0.668	1.713
beta4_pH[9,23]	0.914	0.534	0.276	0.781	2.176
beta4_pH[10,23]	0.714	0.271	0.344	0.667	1.291
beta4_pH[11,23]	0.690	0.247	0.350	0.646	1.196
beta4_pH[12,23]	0.937	0.376	0.438	0.850	1.730
beta4_pH[13,23]	0.746	0.267	0.381	0.695	1.282
beta4_pH[14,23]	1.026	0.338	0.566	0.964	1.707
beta4_pH[15,23]	0.913	0.267	0.538	0.874	1.448
beta4_pH[16,23]	0.904	0.359	0.418	0.827	1.654
beta4_pH[1,24]	0.690	0.276	0.310	0.649	1.274
beta4_pH[2,24]	0.844	0.211	0.544	0.806	1.254
beta4_pH[3,24]	0.905	0.278	0.513	0.870	1.472
beta4_pH[4,24]	0.811	0.268	0.432	0.770	1.339
beta4_pH[5,24]	0.673	0.517	0.089	0.555	1.976
beta4_pH[6,24]	1.935	1.752	0.236	1.368	6.777
beta4_pH[7,24]	1.097	0.609	0.350	0.957	2.493
beta4_pH[8,24]	0.769	0.431	0.226	0.678	1.729
beta4_pH[9,24]	0.922	0.533	0.276	0.783	2.145
beta4_pH[10,24]	0.724	0.274	0.345	0.682	1.290
beta4_pH[11,24]	0.684	0.243	0.353	0.646	1.185
beta4_pH[12,24]	0.934	0.372	0.441	0.845	1.727
beta4_pH[13,24]	0.747	0.268	0.380	0.696	1.289
beta4_pH[14,24]	1.021	0.334	0.560	0.958	1.704
beta4_pH[15,24]	0.914	0.264	0.537	0.872	1.439
beta4_pH[16,24]	0.903	0.358	0.420	0.831	1.652
beta4_pH[1,25]	0.685	0.285	0.305	0.639	1.286
beta4_pH[2,25]	0.846	0.213	0.541	0.815	1.263
beta4_pH[3,25]	0.913	0.284	0.512	0.869	1.467
beta4_pH[4,25]	0.815	0.265	0.429	0.777	1.335
beta4_pH[5,25]	0.642	0.495	0.085	0.525	1.908
beta4_pH[6,25]	1.926	1.720	0.237	1.380	6.676
beta4_pH[7,25]	1.102	0.606	0.350	0.959	2.475
beta4_pH[8,25]	0.772	0.426	0.227	0.690	1.721
beta4_pH[9,25]	0.922	0.534	0.277	0.786	2.155
beta4_pH[10,25]	0.730	0.275	0.346	0.688	1.282
beta4_pH[11,25]	0.690	0.248	0.351	0.646	1.195
beta4_pH[12,25]	0.929	0.377	0.435	0.834	1.740
beta4_pH[13,25]	0.746	0.264	0.379	0.699	1.290
beta4_pH[14,25]	1.029	0.336	0.564	0.970	1.706
beta4_pH[15,25]	0.915	0.265	0.538	0.878	1.432
beta4_pH[16,25]	0.892	0.353	0.420	0.813	1.633
beta4_pH[1,26]	0.692	0.288	0.305	0.658	1.295
beta4_pH[2,26]	0.849	0.214	0.544	0.817	1.263
beta4_pH[3,26]	0.919	0.280	0.514	0.880	1.478
beta4_pH[4,26]	0.811	0.268	0.430	0.782	1.335
beta4_pH[5,26]	0.675	0.526	0.086	0.540	1.976
beta4_pH[6,26]	1.931	1.709	0.231	1.366	6.588
beta4_pH[7,26]	1.101	0.603	0.346	0.968	2.489
beta4_pH[8,26]	0.763	0.426	0.226	0.680	1.719
beta4_pH[9,26]	0.913	0.531	0.274	0.775	2.166
beta4_pH[10,26]	0.728	0.277	0.347	0.686	1.292
beta4_pH[11,26]	0.693	0.244	0.351	0.647	1.191
beta4_pH[12,26]	0.917	0.374	0.437	0.822	1.727
beta4_pH[13,26]	0.746	0.262	0.382	0.698	1.288
beta4_pH[14,26]	1.030	0.331	0.561	0.979	1.694
beta4_pH[15,26]	0.923	0.266	0.536	0.881	1.447
beta4_pH[16,26]	0.898	0.358	0.420	0.822	1.640
beta4_pH[1,27]	0.696	0.285	0.304	0.660	1.287
beta4_pH[2,27]	0.848	0.214	0.541	0.818	1.259
beta4_pH[3,27]	0.915	0.284	0.517	0.870	1.480
beta4_pH[4,27]	0.815	0.265	0.430	0.780	1.339
beta4_pH[5,27]	0.661	0.519	0.085	0.528	1.951
beta4_pH[6,27]	1.941	1.736	0.231	1.350	6.643
beta4_pH[7,27]	1.093	0.608	0.347	0.952	2.449
beta4_pH[8,27]	0.752	0.425	0.228	0.665	1.724
beta4_pH[9,27]	0.911	0.537	0.272	0.775	2.169
beta4_pH[10,27]	0.726	0.276	0.347	0.684	1.293
beta4_pH[11,27]	0.682	0.245	0.349	0.641	1.195
beta4_pH[12,27]	0.936	0.377	0.435	0.855	1.730
beta4_pH[13,27]	0.744	0.262	0.383	0.694	1.287
beta4_pH[14,27]	1.034	0.335	0.560	0.980	1.696
beta4_pH[15,27]	0.921	0.270	0.538	0.877	1.444
beta4_pH[16,27]	0.897	0.359	0.419	0.818	1.649
beta4_pH[1,28]	0.693	0.283	0.306	0.650	1.273
beta4_pH[2,28]	0.851	0.213	0.543	0.824	1.260
beta4_pH[3,28]	0.910	0.279	0.516	0.871	1.469
beta4_pH[4,28]	0.801	0.265	0.429	0.768	1.343
beta4_pH[5,28]	0.680	0.527	0.087	0.554	1.958
beta4_pH[6,28]	1.934	1.709	0.237	1.380	6.626
beta4_pH[7,28]	1.093	0.609	0.348	0.954	2.505
beta4_pH[8,28]	0.768	0.433	0.228	0.681	1.729
beta4_pH[9,28]	0.913	0.536	0.274	0.772	2.181
beta4_pH[10,28]	0.726	0.276	0.350	0.682	1.295
beta4_pH[11,28]	0.693	0.246	0.353	0.647	1.192
beta4_pH[12,28]	0.926	0.383	0.437	0.821	1.732
beta4_pH[13,28]	0.740	0.265	0.380	0.693	1.287
beta4_pH[14,28]	1.034	0.337	0.560	0.978	1.705
beta4_pH[15,28]	0.918	0.265	0.541	0.880	1.450
beta4_pH[16,28]	0.907	0.363	0.419	0.827	1.664
beta4_pH[1,29]	0.691	0.283	0.306	0.641	1.291
beta4_pH[2,29]	0.850	0.211	0.546	0.813	1.258
beta4_pH[3,29]	0.909	0.282	0.514	0.869	1.474
beta4_pH[4,29]	0.813	0.267	0.431	0.780	1.343
beta4_pH[5,29]	0.669	0.513	0.085	0.550	1.962
beta4_pH[6,29]	1.875	1.684	0.226	1.334	6.611
beta4_pH[7,29]	1.081	0.599	0.348	0.948	2.465
beta4_pH[8,29]	0.758	0.426	0.227	0.674	1.709
beta4_pH[9,29]	0.911	0.534	0.276	0.778	2.172
beta4_pH[10,29]	0.717	0.272	0.345	0.669	1.283
beta4_pH[11,29]	0.696	0.248	0.350	0.652	1.189
beta4_pH[12,29]	0.923	0.377	0.435	0.828	1.723
beta4_pH[13,29]	0.750	0.266	0.380	0.704	1.294
beta4_pH[14,29]	1.017	0.330	0.562	0.955	1.692
beta4_pH[15,29]	0.913	0.262	0.536	0.868	1.446
beta4_pH[16,29]	0.899	0.354	0.421	0.832	1.652
beta4_pH[1,30]	0.694	0.289	0.304	0.649	1.286
beta4_pH[2,30]	0.848	0.212	0.546	0.816	1.254
beta4_pH[3,30]	0.916	0.283	0.513	0.876	1.475
beta4_pH[4,30]	0.804	0.265	0.435	0.762	1.351
beta4_pH[5,30]	0.658	0.508	0.087	0.527	1.953
beta4_pH[6,30]	1.882	1.719	0.231	1.300	6.696
beta4_pH[7,30]	1.109	0.609	0.347	0.967	2.467
beta4_pH[8,30]	0.760	0.426	0.225	0.679	1.719
beta4_pH[9,30]	0.925	0.541	0.276	0.784	2.208
beta4_pH[10,30]	0.728	0.274	0.346	0.693	1.287
beta4_pH[11,30]	0.692	0.248	0.352	0.646	1.193
beta4_pH[12,30]	0.922	0.377	0.435	0.823	1.733
beta4_pH[13,30]	0.742	0.269	0.377	0.694	1.301
beta4_pH[14,30]	1.035	0.332	0.559	0.983	1.697
beta4_pH[15,30]	0.906	0.266	0.535	0.860	1.445
beta4_pH[16,30]	0.909	0.359	0.420	0.845	1.659
beta4_pH[1,31]	0.689	0.281	0.305	0.650	1.278
beta4_pH[2,31]	0.853	0.217	0.544	0.817	1.268
beta4_pH[3,31]	0.902	0.278	0.512	0.857	1.461
beta4_pH[4,31]	0.806	0.265	0.431	0.769	1.341
beta4_pH[5,31]	0.685	0.524	0.086	0.567	1.970
beta4_pH[6,31]	1.971	1.774	0.227	1.376	6.821
beta4_pH[7,31]	1.102	0.608	0.346	0.962	2.502
beta4_pH[8,31]	0.761	0.420	0.227	0.672	1.703
beta4_pH[9,31]	0.915	0.536	0.276	0.776	2.168
beta4_pH[10,31]	0.733	0.278	0.344	0.695	1.295
beta4_pH[11,31]	0.690	0.245	0.352	0.646	1.195
beta4_pH[12,31]	0.918	0.369	0.439	0.831	1.715
beta4_pH[13,31]	0.747	0.259	0.382	0.704	1.292
beta4_pH[14,31]	1.019	0.329	0.563	0.963	1.696
beta4_pH[15,31]	0.919	0.270	0.534	0.871	1.436
beta4_pH[16,31]	0.898	0.357	0.416	0.819	1.659
beta4_pH[1,32]	0.690	0.285	0.303	0.642	1.290
beta4_pH[2,32]	0.851	0.211	0.545	0.817	1.261
beta4_pH[3,32]	0.909	0.283	0.513	0.860	1.481
beta4_pH[4,32]	0.805	0.265	0.433	0.768	1.341
beta4_pH[5,32]	0.695	0.526	0.088	0.570	1.956
beta4_pH[6,32]	1.896	1.693	0.228	1.348	6.591
beta4_pH[7,32]	1.114	0.612	0.353	0.978	2.511
beta4_pH[8,32]	0.744	0.414	0.227	0.660	1.685
beta4_pH[9,32]	0.938	0.552	0.277	0.804	2.226
beta4_pH[10,32]	0.718	0.274	0.347	0.674	1.287
beta4_pH[11,32]	0.685	0.241	0.350	0.641	1.182
beta4_pH[12,32]	0.938	0.379	0.436	0.857	1.725
beta4_pH[13,32]	0.744	0.265	0.380	0.693	1.286
beta4_pH[14,32]	1.032	0.336	0.560	0.976	1.711
beta4_pH[15,32]	0.917	0.265	0.537	0.878	1.439
beta4_pH[16,32]	0.912	0.363	0.423	0.836	1.665
beta4_pH[1,33]	0.685	0.282	0.304	0.643	1.285
beta4_pH[2,33]	0.843	0.211	0.546	0.810	1.257
beta4_pH[3,33]	0.901	0.280	0.512	0.858	1.472
beta4_pH[4,33]	0.811	0.265	0.430	0.771	1.348
beta4_pH[5,33]	0.678	0.526	0.086	0.553	1.991
beta4_pH[6,33]	1.922	1.713	0.231	1.355	6.646
beta4_pH[7,33]	1.095	0.605	0.349	0.960	2.473
beta4_pH[8,33]	0.759	0.426	0.227	0.665	1.713
beta4_pH[9,33]	0.909	0.533	0.273	0.775	2.159
beta4_pH[10,33]	0.729	0.277	0.345	0.688	1.289
beta4_pH[11,33]	0.690	0.243	0.353	0.646	1.198
beta4_pH[12,33]	0.933	0.380	0.437	0.845	1.731
beta4_pH[13,33]	0.746	0.266	0.379	0.700	1.290
beta4_pH[14,33]	1.019	0.331	0.563	0.959	1.703
beta4_pH[15,33]	0.922	0.266	0.540	0.874	1.447
beta4_pH[16,33]	0.898	0.362	0.421	0.820	1.658
beta4_pH[1,34]	0.691	0.286	0.306	0.651	1.291
beta4_pH[2,34]	0.850	0.213	0.546	0.821	1.264
beta4_pH[3,34]	0.914	0.280	0.511	0.870	1.475
beta4_pH[4,34]	0.809	0.267	0.431	0.770	1.335
beta4_pH[5,34]	0.660	0.510	0.086	0.545	1.960
beta4_pH[6,34]	1.947	1.745	0.227	1.370	6.623
beta4_pH[7,34]	1.089	0.605	0.347	0.943	2.482
beta4_pH[8,34]	0.761	0.427	0.224	0.673	1.708
beta4_pH[9,34]	0.927	0.533	0.276	0.797	2.167
beta4_pH[10,34]	0.728	0.280	0.346	0.683	1.291
beta4_pH[11,34]	0.688	0.248	0.350	0.644	1.194
beta4_pH[12,34]	0.916	0.368	0.438	0.831	1.712
beta4_pH[13,34]	0.747	0.263	0.380	0.699	1.289
beta4_pH[14,34]	1.021	0.333	0.563	0.961	1.697
beta4_pH[15,34]	0.920	0.267	0.540	0.880	1.444
beta4_pH[16,34]	0.896	0.359	0.419	0.815	1.658
beta4_pH[1,35]	0.415	0.145	0.200	0.391	0.763
beta4_pH[2,35]	0.783	0.086	0.622	0.780	0.963
beta4_pH[3,35]	1.035	0.168	0.737	1.021	1.393
beta4_pH[4,35]	0.592	0.221	0.269	0.549	1.145
beta4_pH[5,35]	0.126	0.095	0.027	0.102	0.362
beta4_pH[6,35]	0.770	0.761	0.132	0.571	2.545
beta4_pH[7,35]	2.265	1.788	0.414	1.802	7.196
beta4_pH[8,35]	0.526	0.260	0.186	0.474	1.180
beta4_pH[9,35]	0.625	0.552	0.100	0.464	2.081
beta4_pH[10,35]	0.632	0.137	0.400	0.620	0.940
beta4_pH[11,35]	0.752	0.197	0.440	0.723	1.216
beta4_pH[12,35]	1.439	0.943	0.373	1.187	3.950
beta4_pH[13,35]	0.725	0.106	0.542	0.717	0.949
beta4_pH[14,35]	0.793	0.272	0.393	0.745	1.445
beta4_pH[15,35]	0.883	0.120	0.668	0.876	1.132
beta4_pH[16,35]	0.598	0.267	0.228	0.556	1.257
beta4_pH[1,36]	0.920	0.205	0.589	0.895	1.389
beta4_pH[2,36]	0.858	0.114	0.658	0.849	1.099
beta4_pH[3,36]	0.871	0.155	0.612	0.855	1.205
beta4_pH[4,36]	0.758	0.228	0.401	0.731	1.278
beta4_pH[5,36]	0.657	0.718	0.074	0.430	2.773
beta4_pH[6,36]	6.094	4.435	0.792	4.902	17.405
beta4_pH[7,36]	1.153	0.664	0.350	0.982	2.826
beta4_pH[8,36]	0.935	0.413	0.370	0.864	1.884
beta4_pH[9,36]	0.533	0.373	0.114	0.441	1.445
beta4_pH[10,36]	0.462	0.128	0.262	0.446	0.762
beta4_pH[11,36]	0.551	0.108	0.367	0.542	0.794
beta4_pH[12,36]	0.857	0.473	0.270	0.750	2.095
beta4_pH[13,36]	0.787	0.123	0.575	0.780	1.046
beta4_pH[14,36]	1.245	0.462	0.588	1.160	2.364
beta4_pH[15,36]	0.959	0.138	0.717	0.951	1.245
beta4_pH[16,36]	1.013	0.395	0.460	0.948	1.958
beta4_pH[1,37]	0.761	0.178	0.477	0.741	1.170
beta4_pH[2,37]	0.772	0.086	0.614	0.769	0.957
beta4_pH[3,37]	0.904	0.133	0.665	0.896	1.189
beta4_pH[4,37]	0.755	0.227	0.394	0.729	1.293
beta4_pH[5,37]	1.127	1.238	0.108	0.734	4.535
beta4_pH[6,37]	2.047	2.009	0.248	1.424	7.448
beta4_pH[7,37]	1.229	0.827	0.311	1.010	3.262
beta4_pH[8,37]	0.974	0.411	0.409	0.897	1.987
beta4_pH[9,37]	1.829	1.961	0.197	1.229	7.356
beta4_pH[10,37]	0.773	0.154	0.522	0.756	1.118
beta4_pH[11,37]	0.836	0.172	0.544	0.817	1.214
beta4_pH[12,37]	0.796	0.515	0.203	0.669	2.162
beta4_pH[13,37]	0.624	0.095	0.457	0.616	0.833
beta4_pH[14,37]	1.011	0.368	0.475	0.957	1.927
beta4_pH[15,37]	0.704	0.102	0.527	0.696	0.929
beta4_pH[16,37]	0.608	0.188	0.320	0.583	1.058
beta4_pH[1,38]	0.740	0.157	0.489	0.725	1.088
beta4_pH[2,38]	0.714	0.084	0.564	0.710	0.888
beta4_pH[3,38]	0.898	0.164	0.613	0.882	1.253
beta4_pH[4,38]	0.905	0.245	0.514	0.876	1.456
beta4_pH[5,38]	0.520	0.425	0.096	0.404	1.608
beta4_pH[6,38]	1.685	2.007	0.134	1.042	7.531
beta4_pH[7,38]	0.502	0.285	0.149	0.437	1.218
beta4_pH[8,38]	0.767	0.307	0.334	0.711	1.509
beta4_pH[9,38]	1.554	1.034	0.360	1.269	4.337
beta4_pH[10,38]	0.720	0.162	0.465	0.702	1.100
beta4_pH[11,38]	0.534	0.136	0.316	0.518	0.848
beta4_pH[12,38]	0.782	0.510	0.208	0.656	2.073
beta4_pH[13,38]	0.915	0.191	0.589	0.897	1.326
beta4_pH[14,38]	1.138	0.436	0.512	1.061	2.214
beta4_pH[15,38]	0.845	0.097	0.665	0.842	1.041
beta4_pH[16,38]	0.830	0.343	0.350	0.770	1.644
beta4_pH[1,39]	0.702	0.144	0.459	0.688	1.015
beta4_pH[2,39]	0.865	0.102	0.678	0.863	1.080
beta4_pH[3,39]	0.837	0.120	0.627	0.830	1.092
beta4_pH[4,39]	0.845	0.283	0.424	0.798	1.503
beta4_pH[5,39]	1.111	1.321	0.113	0.720	4.403
beta4_pH[6,39]	0.481	0.775	0.038	0.272	2.088
beta4_pH[7,39]	1.890	1.719	0.294	1.371	6.580
beta4_pH[8,39]	1.397	0.746	0.436	1.235	3.309
beta4_pH[9,39]	2.042	1.695	0.369	1.551	6.903
beta4_pH[10,39]	0.758	0.205	0.438	0.735	1.238
beta4_pH[11,39]	0.696	0.176	0.410	0.676	1.084
beta4_pH[12,39]	0.783	0.460	0.231	0.679	1.984
beta4_pH[13,39]	0.720	0.119	0.514	0.711	0.980
beta4_pH[14,39]	0.997	0.398	0.451	0.918	1.982
beta4_pH[15,39]	0.996	0.109	0.801	0.990	1.232
beta4_pH[16,39]	0.847	0.340	0.363	0.782	1.656
beta4_pH[1,40]	0.771	0.135	0.540	0.760	1.067
beta4_pH[2,40]	0.763	0.085	0.612	0.759	0.943
beta4_pH[3,40]	0.922	0.144	0.674	0.912	1.241
beta4_pH[4,40]	0.887	0.213	0.545	0.859	1.345
beta4_pH[5,40]	0.323	0.225	0.073	0.263	0.918
beta4_pH[6,40]	2.055	2.129	0.228	1.412	8.178
beta4_pH[7,40]	1.546	1.390	0.263	1.167	5.162
beta4_pH[8,40]	0.354	0.281	0.073	0.280	1.057
beta4_pH[9,40]	0.525	0.571	0.067	0.355	1.921
beta4_pH[10,40]	0.915	0.245	0.531	0.876	1.499
beta4_pH[11,40]	0.467	0.116	0.281	0.451	0.729
beta4_pH[12,40]	0.661	0.403	0.198	0.562	1.707
beta4_pH[13,40]	0.785	0.124	0.574	0.776	1.049
beta4_pH[14,40]	0.760	0.252	0.390	0.725	1.349
beta4_pH[15,40]	0.839	0.096	0.667	0.831	1.045
beta4_pH[16,40]	1.155	0.481	0.480	1.072	2.303
beta4_pH[1,41]	0.610	0.129	0.392	0.600	0.908
beta4_pH[2,41]	0.788	0.104	0.606	0.780	1.008
beta4_pH[3,41]	0.882	0.145	0.629	0.870	1.203
beta4_pH[4,41]	0.860	0.382	0.344	0.783	1.804
beta4_pH[5,41]	1.402	0.772	0.442	1.229	3.344
beta4_pH[6,41]	3.028	3.136	0.297	1.918	12.381
beta4_pH[7,41]	0.828	0.502	0.243	0.704	2.073
beta4_pH[8,41]	1.192	0.715	0.340	1.018	2.972
beta4_pH[9,41]	0.527	0.610	0.058	0.349	2.025
beta4_pH[10,41]	0.775	0.176	0.493	0.753	1.180
beta4_pH[11,41]	0.859	0.243	0.468	0.834	1.403
beta4_pH[12,41]	0.944	0.432	0.346	0.860	2.015
beta4_pH[13,41]	0.700	0.111	0.513	0.691	0.939
beta4_pH[14,41]	1.122	0.351	0.595	1.066	1.953
beta4_pH[15,41]	0.789	0.099	0.607	0.785	1.000
beta4_pH[16,41]	0.916	0.426	0.352	0.828	1.977
beta4_pH[1,42]	0.669	0.140	0.441	0.653	0.988
beta4_pH[2,42]	0.785	0.098	0.610	0.778	0.988
beta4_pH[3,42]	0.800	0.151	0.542	0.786	1.132
beta4_pH[4,42]	0.969	0.310	0.485	0.921	1.693
beta4_pH[5,42]	1.437	1.588	0.147	0.915	5.801
beta4_pH[6,42]	0.335	0.262	0.064	0.261	1.060
beta4_pH[7,42]	0.990	0.627	0.262	0.836	2.580
beta4_pH[8,42]	0.775	0.344	0.325	0.704	1.644
beta4_pH[9,42]	0.781	0.563	0.168	0.631	2.255
beta4_pH[10,42]	0.914	0.207	0.575	0.891	1.396
beta4_pH[11,42]	0.641	0.147	0.409	0.627	0.964
beta4_pH[12,42]	0.827	0.389	0.313	0.748	1.788
beta4_pH[13,42]	0.516	0.164	0.268	0.493	0.903
beta4_pH[14,42]	0.900	0.307	0.436	0.850	1.624
beta4_pH[15,42]	0.923	0.094	0.752	0.919	1.125
beta4_pH[16,42]	0.569	0.207	0.277	0.533	1.074
beta4_pH[1,43]	0.798	0.194	0.482	0.774	1.254
beta4_pH[2,43]	0.754	0.081	0.612	0.750	0.922
beta4_pH[3,43]	0.670	0.095	0.506	0.663	0.872
beta4_pH[4,43]	0.854	0.283	0.428	0.811	1.539
beta4_pH[5,43]	1.588	0.728	0.618	1.452	3.421
beta4_pH[6,43]	1.141	0.960	0.230	0.877	3.683
beta4_pH[7,43]	0.727	0.650	0.135	0.550	2.314
beta4_pH[8,43]	0.635	0.287	0.254	0.578	1.331
beta4_pH[9,43]	1.164	1.073	0.166	0.835	3.900
beta4_pH[10,43]	0.678	0.141	0.448	0.662	1.011
beta4_pH[11,43]	0.640	0.136	0.418	0.624	0.941
beta4_pH[12,43]	0.761	0.378	0.269	0.685	1.680
beta4_pH[13,43]	0.585	0.120	0.387	0.573	0.852
beta4_pH[14,43]	1.101	0.338	0.576	1.053	1.887
beta4_pH[15,43]	0.849	0.103	0.667	0.845	1.073
beta4_pH[16,43]	1.232	0.460	0.572	1.147	2.319
beta4_pH[1,44]	0.610	0.164	0.353	0.590	0.982
beta4_pH[2,44]	0.704	0.079	0.564	0.699	0.870
beta4_pH[3,44]	0.637	0.100	0.464	0.630	0.852
beta4_pH[4,44]	0.833	0.211	0.490	0.807	1.319
beta4_pH[5,44]	1.264	0.605	0.472	1.143	2.834
beta4_pH[6,44]	1.269	1.465	0.128	0.809	5.287
beta4_pH[7,44]	1.162	0.664	0.361	1.005	2.792
beta4_pH[8,44]	0.441	0.284	0.116	0.368	1.201
beta4_pH[9,44]	0.986	0.848	0.153	0.750	3.110
beta4_pH[10,44]	0.630	0.155	0.382	0.607	0.979
beta4_pH[11,44]	0.357	0.126	0.172	0.335	0.659
beta4_pH[12,44]	0.608	0.326	0.202	0.539	1.445
beta4_pH[13,44]	0.541	0.099	0.373	0.536	0.756
beta4_pH[14,44]	0.682	0.176	0.400	0.661	1.069
beta4_pH[15,44]	0.644	0.084	0.496	0.637	0.822
beta4_pH[16,44]	0.434	0.189	0.171	0.397	0.896
beta4_pH[1,45]	0.799	0.193	0.489	0.779	1.226
beta4_pH[2,45]	0.710	0.085	0.559	0.704	0.892
beta4_pH[3,45]	0.765	0.142	0.518	0.751	1.077
beta4_pH[4,45]	0.755	0.197	0.444	0.729	1.201
beta4_pH[5,45]	0.962	1.101	0.096	0.629	3.770
beta4_pH[6,45]	1.226	1.261	0.169	0.879	4.243
beta4_pH[7,45]	0.702	0.579	0.128	0.545	2.261
beta4_pH[8,45]	1.188	0.530	0.481	1.086	2.519
beta4_pH[9,45]	0.104	0.118	0.011	0.068	0.411
beta4_pH[10,45]	0.852	0.204	0.519	0.833	1.319
beta4_pH[11,45]	0.472	0.102	0.306	0.459	0.709
beta4_pH[12,45]	0.775	0.355	0.298	0.709	1.627
beta4_pH[13,45]	0.461	0.077	0.329	0.455	0.633
beta4_pH[14,45]	0.740	0.172	0.458	0.723	1.135
beta4_pH[15,45]	0.507	0.068	0.388	0.502	0.650
beta4_pH[16,45]	0.263	0.170	0.074	0.224	0.688
beta4_pH[1,46]	0.799	0.160	0.525	0.786	1.143
beta4_pH[2,46]	0.681	0.096	0.511	0.677	0.892
beta4_pH[3,46]	0.763	0.116	0.560	0.754	1.022
beta4_pH[4,46]	0.877	0.329	0.405	0.821	1.639
beta4_pH[5,46]	1.126	0.605	0.355	0.993	2.614
beta4_pH[6,46]	1.512	1.826	0.118	0.906	6.389
beta4_pH[7,46]	1.651	1.169	0.353	1.336	4.727
beta4_pH[8,46]	1.075	0.499	0.413	0.973	2.296
beta4_pH[9,46]	1.657	1.654	0.203	1.139	6.160
beta4_pH[10,46]	0.667	0.178	0.383	0.646	1.090
beta4_pH[11,46]	0.700	0.160	0.438	0.680	1.056
beta4_pH[12,46]	1.175	0.628	0.401	1.037	2.778
beta4_pH[13,46]	0.593	0.183	0.310	0.565	1.021
beta4_pH[14,46]	0.975	0.340	0.465	0.928	1.761
beta4_pH[15,46]	0.623	0.076	0.481	0.617	0.783
beta4_pH[16,46]	0.624	0.276	0.254	0.567	1.297
beta4_pH[1,47]	0.630	0.148	0.389	0.613	0.950
beta4_pH[2,47]	0.767	0.110	0.575	0.761	0.995
beta4_pH[3,47]	0.770	0.117	0.573	0.762	1.029
beta4_pH[4,47]	0.543	0.220	0.231	0.501	1.092
beta4_pH[5,47]	0.115	0.082	0.025	0.094	0.331
beta4_pH[6,47]	0.189	0.137	0.043	0.152	0.538
beta4_pH[7,47]	0.490	0.437	0.082	0.371	1.642
beta4_pH[8,47]	0.859	0.564	0.213	0.716	2.279
beta4_pH[9,47]	0.467	0.560	0.040	0.294	2.031
beta4_pH[10,47]	0.841	0.272	0.428	0.798	1.483
beta4_pH[11,47]	0.588	0.119	0.386	0.577	0.858
beta4_pH[12,47]	1.629	0.950	0.507	1.414	4.057
beta4_pH[13,47]	0.682	0.118	0.481	0.668	0.953
beta4_pH[14,47]	0.872	0.329	0.399	0.814	1.690
beta4_pH[15,47]	0.714	0.121	0.511	0.701	0.989
beta4_pH[16,47]	0.810	0.327	0.348	0.750	1.640
beta0_pelagic[1]	2.250	0.140	1.970	2.249	2.523
beta0_pelagic[2]	1.483	0.132	1.215	1.481	1.742
beta0_pelagic[3]	0.172	0.370	-0.844	0.234	0.707
beta0_pelagic[4]	0.335	0.323	-0.327	0.341	0.950
beta0_pelagic[5]	1.427	0.212	1.005	1.425	1.845
beta0_pelagic[6]	1.361	0.154	1.057	1.360	1.662
beta0_pelagic[7]	1.511	0.144	1.224	1.513	1.790
beta0_pelagic[8]	1.749	0.144	1.465	1.749	2.030
beta0_pelagic[9]	2.656	0.167	2.333	2.653	2.985
beta0_pelagic[10]	2.531	0.134	2.268	2.530	2.795
beta0_pelagic[11]	-0.418	0.323	-1.103	-0.398	0.188
beta0_pelagic[12]	1.721	0.145	1.436	1.722	2.003
beta0_pelagic[13]	0.349	0.347	-0.798	0.411	0.769
beta0_pelagic[14]	-0.191	0.265	-0.773	-0.168	0.257
beta0_pelagic[15]	-0.263	0.185	-0.672	-0.250	0.045
beta0_pelagic[16]	-0.439	0.323	-1.132	-0.429	0.160
beta1_pelagic[1]	0.000	0.000	0.000	0.000	0.000
beta1_pelagic[2]	0.000	0.000	0.000	0.000	0.000
beta1_pelagic[3]	0.734	0.463	0.067	0.658	2.202
beta1_pelagic[4]	0.780	0.350	0.065	0.788	1.469
beta1_pelagic[5]	0.000	0.000	0.000	0.000	0.000
beta1_pelagic[6]	0.000	0.000	0.000	0.000	0.000
beta1_pelagic[7]	0.000	0.000	0.000	0.000	0.000
beta1_pelagic[8]	0.000	0.000	0.000	0.000	0.000
beta1_pelagic[9]	0.000	0.000	0.000	0.000	0.000
beta1_pelagic[10]	0.000	0.000	0.000	0.000	0.000
beta1_pelagic[11]	1.516	0.397	0.743	1.509	2.331
beta1_pelagic[12]	0.000	0.000	0.000	0.000	0.000
beta1_pelagic[13]	0.662	0.554	0.014	0.582	2.232
beta1_pelagic[14]	1.482	0.479	0.751	1.396	2.676
beta1_pelagic[15]	0.130	0.186	0.011	0.056	0.649
beta1_pelagic[16]	1.514	0.439	0.749	1.468	2.513
beta2_pelagic[1]	0.000	0.000	0.000	0.000	0.000
beta2_pelagic[2]	0.000	0.000	0.000	0.000	0.000
beta2_pelagic[3]	6.894	6.153	0.115	5.304	21.950
beta2_pelagic[4]	7.353	5.883	0.375	5.919	21.863
beta2_pelagic[5]	0.000	0.000	0.000	0.000	0.000
beta2_pelagic[6]	0.000	0.000	0.000	0.000	0.000
beta2_pelagic[7]	0.000	0.000	0.000	0.000	0.000
beta2_pelagic[8]	0.000	0.000	0.000	0.000	0.000
beta2_pelagic[9]	0.000	0.000	0.000	0.000	0.000
beta2_pelagic[10]	0.000	0.000	0.000	0.000	0.000
beta2_pelagic[11]	2.111	1.677	0.280	1.614	6.371
beta2_pelagic[12]	0.000	0.000	0.000	0.000	0.000
beta2_pelagic[13]	2.128	1.816	0.108	1.634	6.555
beta2_pelagic[14]	1.443	1.466	0.189	0.867	5.540
beta2_pelagic[15]	2.449	1.886	0.074	2.071	6.987
beta2_pelagic[16]	1.666	1.605	0.190	1.068	5.946
beta3_pelagic[1]	28.998	6.361	18.558	29.042	39.456
beta3_pelagic[2]	28.927	6.322	18.657	28.887	39.462
beta3_pelagic[3]	28.036	3.667	20.810	28.429	35.595
beta3_pelagic[4]	25.926	2.882	21.381	25.946	34.716
beta3_pelagic[5]	29.222	6.399	18.526	29.316	39.487
beta3_pelagic[6]	29.104	6.338	18.613	28.997	39.398
beta3_pelagic[7]	28.849	6.349	18.516	28.845	39.243
beta3_pelagic[8]	28.787	6.411	18.463	28.572	39.363
beta3_pelagic[9]	28.912	6.284	18.590	28.911	39.448
beta3_pelagic[10]	28.834	6.349	18.539	28.604	39.506
beta3_pelagic[11]	29.627	1.317	26.881	29.642	32.197
beta3_pelagic[12]	28.972	6.336	18.482	28.838	39.466
beta3_pelagic[13]	33.956	5.335	19.941	35.592	39.776
beta3_pelagic[14]	34.325	2.052	30.722	34.203	39.037
beta3_pelagic[15]	29.964	6.602	18.717	30.736	39.726
beta3_pelagic[16]	31.144	1.888	27.879	30.917	35.892
beta0_yellow[1]	-0.509	0.161	-0.825	-0.508	-0.191
beta0_yellow[2]	0.572	0.215	0.188	0.588	0.907
beta0_yellow[3]	-0.150	0.206	-0.565	-0.144	0.225
beta0_yellow[4]	0.920	0.353	-0.151	0.992	1.344
beta0_yellow[5]	0.415	0.347	-0.376	0.469	0.956
beta0_yellow[6]	0.813	0.165	0.484	0.810	1.144
beta0_yellow[7]	0.923	0.163	0.628	0.913	1.261
beta0_yellow[8]	0.973	0.167	0.664	0.966	1.312
beta0_yellow[9]	0.575	0.170	0.230	0.581	0.891
beta0_yellow[10]	0.700	0.140	0.422	0.699	0.973
beta0_yellow[11]	0.194	0.173	-0.149	0.192	0.529
beta0_yellow[12]	-1.132	0.180	-1.490	-1.133	-0.776
beta0_yellow[13]	-0.844	0.171	-1.194	-0.838	-0.512
beta0_yellow[14]	0.023	0.177	-0.326	0.025	0.371
beta0_yellow[15]	-0.789	0.168	-1.114	-0.789	-0.455
beta0_yellow[16]	-0.241	0.173	-0.575	-0.242	0.097
beta1_yellow[1]	0.000	0.000	0.000	0.000	0.000
beta1_yellow[2]	1.004	0.426	0.464	0.950	1.827
beta1_yellow[3]	0.426	0.300	0.014	0.419	0.983
beta1_yellow[4]	1.305	0.766	0.491	1.128	3.936
beta1_yellow[5]	0.000	0.000	0.000	0.000	0.000
beta1_yellow[6]	0.000	0.000	0.000	0.000	0.000
beta1_yellow[7]	0.000	0.000	0.000	0.000	0.000
beta1_yellow[8]	0.000	0.000	0.000	0.000	0.000
beta1_yellow[9]	0.000	0.000	0.000	0.000	0.000
beta1_yellow[10]	0.000	0.000	0.000	0.000	0.000
beta1_yellow[11]	0.000	0.000	0.000	0.000	0.000
beta1_yellow[12]	0.000	0.000	0.000	0.000	0.000
beta1_yellow[13]	0.000	0.000	0.000	0.000	0.000
beta1_yellow[14]	0.000	0.000	0.000	0.000	0.000
beta1_yellow[15]	0.000	0.000	0.000	0.000	0.000
beta1_yellow[16]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[1]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[2]	-7.326	5.886	-21.581	-5.919	-0.205
beta2_yellow[3]	-7.863	5.873	-20.961	-6.510	-0.359
beta2_yellow[4]	-6.135	5.720	-19.796	-4.643	-0.096
beta2_yellow[5]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[6]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[7]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[8]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[9]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[10]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[11]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[12]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[13]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[14]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[15]	0.000	0.000	0.000	0.000	0.000
beta2_yellow[16]	0.000	0.000	0.000	0.000	0.000
beta3_yellow[1]	25.000	0.000	25.000	25.000	25.000
beta3_yellow[2]	29.049	1.833	26.467	28.784	32.894
beta3_yellow[3]	32.450	4.052	21.575	32.705	40.264
beta3_yellow[4]	28.581	3.343	22.099	27.752	36.077
beta3_yellow[5]	25.000	0.000	25.000	25.000	25.000
beta3_yellow[6]	25.000	0.000	25.000	25.000	25.000
beta3_yellow[7]	25.000	0.000	25.000	25.000	25.000
beta3_yellow[8]	25.000	0.000	25.000	25.000	25.000
beta3_yellow[9]	25.000	0.000	25.000	25.000	25.000
beta3_yellow[10]	25.000	0.000	25.000	25.000	25.000
beta3_yellow[11]	25.000	0.000	25.000	25.000	25.000
beta3_yellow[12]	25.000	0.000	25.000	25.000	25.000
beta3_yellow[13]	25.000	0.000	25.000	25.000	25.000
beta3_yellow[14]	25.000	0.000	25.000	25.000	25.000
beta3_yellow[15]	25.000	0.000	25.000	25.000	25.000
beta3_yellow[16]	25.000	0.000	25.000	25.000	25.000
beta0_black[1]	-0.004	0.153	-0.296	-0.006	0.302
beta0_black[2]	1.891	0.135	1.632	1.892	2.158
beta0_black[3]	1.367	0.141	1.081	1.370	1.648
beta0_black[4]	2.488	0.141	2.209	2.489	2.767
beta0_black[5]	4.549	2.166	1.776	4.060	10.351
beta0_black[6]	4.421	2.006	2.119	3.867	9.892
beta0_black[7]	3.240	1.797	1.270	2.755	8.321
beta0_black[8]	0.899	0.235	0.461	0.892	1.353
beta0_black[9]	2.585	0.256	2.097	2.581	3.092
beta0_black[10]	1.376	0.138	1.105	1.373	1.643
beta0_black[11]	3.470	0.174	3.133	3.470	3.812
beta0_black[12]	4.848	0.195	4.456	4.854	5.225
beta0_black[13]	0.249	0.186	0.010	0.210	0.683
beta0_black[14]	2.985	0.179	2.618	2.987	3.325
beta0_black[15]	1.405	0.169	1.085	1.405	1.737
beta0_black[16]	4.243	0.185	3.880	4.240	4.596
beta2_black[1]	0.000	0.000	0.000	0.000	0.000
beta2_black[2]	0.000	0.000	0.000	0.000	0.000
beta2_black[3]	0.000	0.000	0.000	0.000	0.000
beta2_black[4]	0.000	0.000	0.000	0.000	0.000
beta2_black[5]	0.000	0.000	0.000	0.000	0.000
beta2_black[6]	0.000	0.000	0.000	0.000	0.000
beta2_black[7]	0.000	0.000	0.000	0.000	0.000
beta2_black[8]	0.000	0.000	0.000	0.000	0.000
beta2_black[9]	0.000	0.000	0.000	0.000	0.000
beta2_black[10]	0.000	0.000	0.000	0.000	0.000
beta2_black[11]	0.000	0.000	0.000	0.000	0.000
beta2_black[12]	0.000	0.000	0.000	0.000	0.000
beta2_black[13]	-2.818	1.959	-7.804	-2.254	-0.521
beta2_black[14]	0.000	0.000	0.000	0.000	0.000
beta2_black[15]	0.000	0.000	0.000	0.000	0.000
beta2_black[16]	0.000	0.000	0.000	0.000	0.000
beta3_black[1]	25.000	0.000	25.000	25.000	25.000
beta3_black[2]	25.000	0.000	25.000	25.000	25.000
beta3_black[3]	25.000	0.000	25.000	25.000	25.000
beta3_black[4]	25.000	0.000	25.000	25.000	25.000
beta3_black[5]	25.000	0.000	25.000	25.000	25.000
beta3_black[6]	25.000	0.000	25.000	25.000	25.000
beta3_black[7]	25.000	0.000	25.000	25.000	25.000
beta3_black[8]	25.000	0.000	25.000	25.000	25.000
beta3_black[9]	25.000	0.000	25.000	25.000	25.000
beta3_black[10]	25.000	0.000	25.000	25.000	25.000
beta3_black[11]	25.000	0.000	25.000	25.000	25.000
beta3_black[12]	25.000	0.000	25.000	25.000	25.000
beta3_black[13]	38.975	0.959	36.939	39.138	40.317
beta3_black[14]	25.000	0.000	25.000	25.000	25.000
beta3_black[15]	25.000	0.000	25.000	25.000	25.000
beta3_black[16]	25.000	0.000	25.000	25.000	25.000
beta4_black[1]	-0.261	0.202	-0.665	-0.264	0.131
beta4_black[2]	0.267	0.189	-0.098	0.265	0.630
beta4_black[3]	-1.000	0.198	-1.392	-0.996	-0.622
beta4_black[4]	0.490	0.217	0.060	0.490	0.921
beta4_black[5]	0.707	1.448	-1.151	0.408	4.184
beta4_black[6]	0.850	1.487	-0.885	0.527	4.491
beta4_black[7]	0.684	1.452	-0.986	0.400	4.012
beta4_black[8]	-0.222	0.319	-0.857	-0.223	0.384
beta4_black[9]	0.949	0.852	-0.217	0.774	3.013
beta4_black[10]	0.061	0.187	-0.307	0.057	0.422
beta4_black[11]	-0.718	0.227	-1.168	-0.721	-0.278
beta4_black[12]	0.421	0.344	-0.246	0.417	1.109
beta4_black[13]	-1.345	0.219	-1.758	-1.349	-0.921
beta4_black[14]	-0.111	0.253	-0.592	-0.107	0.378
beta4_black[15]	-0.926	0.225	-1.347	-0.928	-0.483
beta4_black[16]	-0.603	0.247	-1.087	-0.600	-0.135
beta0_dsr[11]	1.894	0.171	1.556	1.892	2.210
beta0_dsr[12]	4.982	0.277	4.457	4.976	5.542
beta0_dsr[13]	1.515	0.172	1.180	1.511	1.863
beta0_dsr[14]	2.622	0.181	2.268	2.623	2.970
beta0_dsr[15]	1.332	0.169	1.005	1.330	1.656
beta0_dsr[16]	2.832	0.178	2.481	2.832	3.181
beta1_dsr[11]	0.000	0.000	0.000	0.000	0.000
beta1_dsr[12]	0.000	0.000	0.000	0.000	0.000
beta1_dsr[13]	0.000	0.000	0.000	0.000	0.000
beta1_dsr[14]	0.000	0.000	0.000	0.000	0.000
beta1_dsr[15]	0.000	0.000	0.000	0.000	0.000
beta1_dsr[16]	0.000	0.000	0.000	0.000	0.000
beta4_dsr[11]	0.657	0.236	0.189	0.656	1.102
beta4_dsr[12]	0.000	0.744	-1.328	-0.056	1.586
beta4_dsr[13]	-0.311	0.235	-0.772	-0.312	0.143
beta4_dsr[14]	0.052	0.282	-0.500	0.056	0.593
beta4_dsr[15]	0.832	0.225	0.399	0.830	1.267
beta4_dsr[16]	0.089	0.252	-0.412	0.089	0.580
beta0_slope[11]	-1.826	0.171	-2.157	-1.825	-1.493
beta0_slope[12]	-4.753	0.254	-5.255	-4.749	-4.263
beta0_slope[13]	-1.261	0.175	-1.610	-1.260	-0.926
beta0_slope[14]	-2.630	0.189	-3.001	-2.631	-2.263
beta0_slope[15]	-1.262	0.169	-1.596	-1.260	-0.939
beta0_slope[16]	-2.680	0.183	-3.043	-2.674	-2.333
beta1_slope[11]	0.000	0.000	0.000	0.000	0.000
beta1_slope[12]	0.000	0.000	0.000	0.000	0.000
beta1_slope[13]	0.000	0.000	0.000	0.000	0.000
beta1_slope[14]	0.000	0.000	0.000	0.000	0.000
beta1_slope[15]	0.000	0.000	0.000	0.000	0.000
beta1_slope[16]	0.000	0.000	0.000	0.000	0.000
beta4_slope[11]	-0.811	0.231	-1.266	-0.807	-0.372
beta4_slope[12]	-1.602	0.601	-2.807	-1.582	-0.493
beta4_slope[13]	0.086	0.232	-0.358	0.087	0.545
beta4_slope[14]	0.014	0.280	-0.529	0.015	0.547
beta4_slope[15]	-0.875	0.229	-1.317	-0.877	-0.416
beta4_slope[16]	-0.233	0.249	-0.716	-0.231	0.246
beta5_slope[11]	2.679	0.288	2.123	2.679	3.254
beta5_slope[12]	-0.206	0.473	-1.125	-0.207	0.722
beta5_slope[13]	1.235	0.281	0.695	1.234	1.802
beta5_slope[14]	4.047	0.515	3.069	4.041	5.072
beta5_slope[15]	1.739	0.279	1.212	1.737	2.291
beta5_slope[16]	2.686	0.358	1.968	2.680	3.391
sigma_H[1]	0.194	0.056	0.090	0.190	0.310
sigma_H[2]	0.171	0.030	0.118	0.169	0.236
sigma_H[3]	0.204	0.043	0.127	0.203	0.298
sigma_H[4]	0.351	0.072	0.226	0.345	0.508
sigma_H[5]	1.033	0.239	0.598	1.021	1.534
sigma_H[6]	0.273	0.190	0.013	0.244	0.724
sigma_H[7]	0.276	0.049	0.195	0.271	0.391
sigma_H[8]	0.435	0.091	0.302	0.422	0.634
sigma_H[9]	0.394	0.077	0.274	0.386	0.573
sigma_H[10]	0.227	0.046	0.148	0.223	0.332
sigma_H[11]	0.276	0.045	0.200	0.273	0.375
sigma_H[12]	0.466	0.173	0.208	0.462	0.804
sigma_H[13]	0.208	0.037	0.143	0.206	0.290
sigma_H[14]	0.466	0.097	0.305	0.456	0.684
sigma_H[15]	0.247	0.040	0.182	0.244	0.338
sigma_H[16]	0.227	0.044	0.153	0.222	0.326
lambda_H[1]	2.931	4.033	0.146	1.533	14.271
lambda_H[2]	8.562	8.153	0.904	6.218	29.467
lambda_H[3]	7.197	10.224	0.318	3.822	35.083
lambda_H[4]	0.008	0.006	0.002	0.007	0.023
lambda_H[5]	3.129	8.685	0.014	0.371	27.215
lambda_H[6]	11.015	19.288	0.016	4.243	57.103
lambda_H[7]	0.017	0.012	0.003	0.014	0.047
lambda_H[8]	8.194	10.304	0.001	4.755	38.232
lambda_H[9]	0.020	0.014	0.004	0.017	0.055
lambda_H[10]	0.385	1.434	0.033	0.191	1.516
lambda_H[11]	0.274	0.400	0.012	0.136	1.283
lambda_H[12]	5.595	7.193	0.239	3.237	25.117
lambda_H[13]	3.843	3.602	0.275	2.827	14.027
lambda_H[14]	3.343	4.061	0.237	2.139	13.739
lambda_H[15]	0.028	0.041	0.004	0.018	0.112
lambda_H[16]	0.914	1.754	0.027	0.313	5.469
mu_lambda_H[1]	4.412	1.890	1.237	4.255	8.498
mu_lambda_H[2]	3.964	1.982	0.697	3.813	8.302
mu_lambda_H[3]	3.588	1.862	0.756	3.315	7.742
sigma_lambda_H[1]	8.690	4.334	2.139	7.995	18.199
sigma_lambda_H[2]	8.575	4.681	1.083	8.030	18.573
sigma_lambda_H[3]	6.457	4.075	0.981	5.552	16.677
beta_H[1,1]	6.819	1.099	4.279	6.994	8.450
beta_H[2,1]	9.874	0.479	8.853	9.895	10.731
beta_H[3,1]	8.036	0.741	6.276	8.115	9.276
beta_H[4,1]	12.386	7.549	-3.014	12.300	27.352
beta_H[5,1]	0.034	3.141	-6.456	0.227	5.993
beta_H[6,1]	4.332	2.832	-3.791	5.087	7.447
beta_H[7,1]	2.290	5.307	-9.100	2.655	11.852
beta_H[8,1]	3.040	9.777	-2.399	1.295	42.729
beta_H[9,1]	13.689	5.420	3.964	13.293	25.728
beta_H[10,1]	7.182	1.741	3.660	7.230	10.604
beta_H[11,1]	5.203	3.485	-2.816	5.956	9.963
beta_H[12,1]	2.579	0.979	0.849	2.517	4.693
beta_H[13,1]	8.982	0.863	6.992	9.051	10.380
beta_H[14,1]	2.194	1.024	0.072	2.222	4.210
beta_H[15,1]	-5.775	3.876	-12.740	-6.055	2.469
beta_H[16,1]	4.175	3.114	-0.540	3.643	11.821
beta_H[1,2]	7.909	0.254	7.380	7.920	8.382
beta_H[2,2]	10.031	0.137	9.756	10.030	10.298
beta_H[3,2]	8.954	0.201	8.562	8.954	9.357
beta_H[4,2]	2.413	1.491	-0.511	2.388	5.487
beta_H[5,2]	1.962	1.132	-0.320	1.973	4.089
beta_H[6,2]	5.991	0.895	3.846	6.106	7.403
beta_H[7,2]	2.095	1.019	0.286	2.012	4.277
beta_H[8,2]	2.576	2.351	-7.054	3.090	4.193
beta_H[9,2]	2.856	1.012	0.874	2.874	4.826
beta_H[10,2]	8.123	0.360	7.339	8.148	8.779
beta_H[11,2]	9.753	0.622	8.868	9.637	11.159
beta_H[12,2]	3.953	0.354	3.295	3.946	4.649
beta_H[13,2]	9.130	0.242	8.684	9.119	9.626
beta_H[14,2]	4.059	0.353	3.370	4.054	4.738
beta_H[15,2]	11.296	0.691	9.843	11.314	12.596
beta_H[16,2]	4.702	0.852	3.115	4.655	6.492
beta_H[1,3]	8.552	0.252	8.093	8.549	9.065
beta_H[2,3]	10.107	0.114	9.891	10.109	10.339
beta_H[3,3]	9.655	0.165	9.331	9.649	9.995
beta_H[4,3]	-0.839	1.187	-3.088	-0.922	1.690
beta_H[5,3]	4.168	0.759	2.632	4.163	5.629
beta_H[6,3]	7.518	0.945	6.249	7.292	10.058
beta_H[7,3]	-2.151	0.670	-3.556	-2.134	-0.861
beta_H[8,3]	5.381	1.099	4.563	5.136	9.857
beta_H[9,3]	-1.756	0.721	-3.196	-1.749	-0.334
beta_H[10,3]	8.856	0.291	8.286	8.861	9.449
beta_H[11,3]	8.549	0.284	7.939	8.575	9.038
beta_H[12,3]	5.320	0.311	4.584	5.361	5.828
beta_H[13,3]	8.943	0.176	8.587	8.944	9.287
beta_H[14,3]	5.816	0.277	5.227	5.827	6.314
beta_H[15,3]	10.405	0.320	9.774	10.406	11.019
beta_H[16,3]	5.996	0.897	4.121	6.078	7.506
beta_H[1,4]	8.304	0.179	7.919	8.319	8.617
beta_H[2,4]	10.164	0.116	9.917	10.169	10.363
beta_H[3,4]	10.155	0.156	9.817	10.168	10.424
beta_H[4,4]	11.516	0.426	10.657	11.510	12.351
beta_H[5,4]	6.027	0.994	4.465	5.913	8.201
beta_H[6,4]	7.489	0.691	5.560	7.633	8.430
beta_H[7,4]	8.135	0.323	7.491	8.133	8.778
beta_H[8,4]	6.600	0.420	5.100	6.667	7.084
beta_H[9,4]	6.905	0.383	6.126	6.904	7.671
beta_H[10,4]	7.789	0.263	7.317	7.776	8.365
beta_H[11,4]	9.379	0.198	8.993	9.377	9.763
beta_H[12,4]	7.141	0.215	6.716	7.140	7.585
beta_H[13,4]	9.073	0.144	8.778	9.078	9.347
beta_H[14,4]	7.796	0.211	7.373	7.798	8.192
beta_H[15,4]	9.466	0.232	8.994	9.467	9.924
beta_H[16,4]	9.399	0.297	8.877	9.376	10.024
beta_H[1,5]	8.986	0.145	8.695	8.987	9.272
beta_H[2,5]	10.778	0.094	10.596	10.778	10.969
beta_H[3,5]	10.889	0.165	10.593	10.885	11.243
beta_H[4,5]	8.481	0.399	7.713	8.483	9.263
beta_H[5,5]	5.016	0.867	3.040	5.181	6.348
beta_H[6,5]	8.576	0.477	7.854	8.504	9.816
beta_H[7,5]	6.832	0.312	6.214	6.836	7.440
beta_H[8,5]	8.257	0.329	7.848	8.203	9.368
beta_H[9,5]	8.366	0.375	7.607	8.374	9.099
beta_H[10,5]	10.065	0.245	9.553	10.071	10.530
beta_H[11,5]	11.505	0.231	11.053	11.506	11.973
beta_H[12,5]	8.470	0.197	8.090	8.466	8.859
beta_H[13,5]	10.006	0.127	9.746	10.008	10.248
beta_H[14,5]	9.221	0.219	8.801	9.211	9.706
beta_H[15,5]	11.160	0.244	10.693	11.158	11.651
beta_H[16,5]	9.893	0.195	9.470	9.906	10.254
beta_H[1,6]	10.180	0.196	9.857	10.163	10.614
beta_H[2,6]	11.512	0.102	11.315	11.513	11.714
beta_H[3,6]	10.825	0.159	10.502	10.830	11.112
beta_H[4,6]	12.804	0.693	11.377	12.813	14.173
beta_H[5,6]	6.063	0.752	4.761	6.021	7.716
beta_H[6,6]	8.818	0.488	7.653	8.870	9.556
beta_H[7,6]	9.784	0.508	8.781	9.785	10.787
beta_H[8,6]	9.463	0.456	7.950	9.531	9.989
beta_H[9,6]	8.347	0.617	7.166	8.320	9.571
beta_H[10,6]	9.534	0.327	8.852	9.551	10.122
beta_H[11,6]	10.816	0.351	10.049	10.844	11.443
beta_H[12,6]	9.387	0.263	8.892	9.378	9.939
beta_H[13,6]	11.047	0.162	10.758	11.042	11.394
beta_H[14,6]	9.816	0.280	9.243	9.818	10.359
beta_H[15,6]	10.840	0.424	9.973	10.848	11.665
beta_H[16,6]	10.545	0.264	9.996	10.554	11.068
beta_H[1,7]	10.826	0.929	8.509	10.949	12.231
beta_H[2,7]	12.214	0.414	11.320	12.226	13.027
beta_H[3,7]	10.605	0.630	9.187	10.676	11.629
beta_H[4,7]	2.711	3.596	-4.299	2.622	10.094
beta_H[5,7]	7.124	2.764	2.618	6.772	13.858
beta_H[6,7]	9.304	1.623	5.906	9.324	12.630
beta_H[7,7]	10.823	2.563	5.813	10.824	16.086
beta_H[8,7]	11.220	1.828	9.337	10.971	16.973
beta_H[9,7]	4.734	3.139	-1.410	4.764	10.676
beta_H[10,7]	9.807	1.488	7.085	9.718	12.987
beta_H[11,7]	10.973	1.697	7.863	10.837	14.776
beta_H[12,7]	10.093	0.900	8.194	10.164	11.692
beta_H[13,7]	11.678	0.730	9.912	11.771	12.838
beta_H[14,7]	10.372	0.901	8.445	10.404	11.964
beta_H[15,7]	11.993	2.217	7.629	11.945	16.417
beta_H[16,7]	12.329	1.391	9.971	12.149	15.436
beta0_H[1]	8.499	14.360	-21.904	8.908	36.793
beta0_H[2]	10.517	6.115	-1.614	10.656	23.408
beta0_H[3]	9.763	9.238	-8.606	9.904	28.278
beta0_H[4]	3.972	166.716	-328.836	1.213	349.552
beta0_H[5]	3.733	38.584	-82.995	4.714	80.576
beta0_H[6]	7.821	29.505	-49.950	7.576	67.428
beta0_H[7]	5.405	120.206	-235.036	4.076	254.368
beta0_H[8]	5.887	83.559	-40.078	6.395	45.416
beta0_H[9]	10.206	105.293	-198.677	9.230	233.884
beta0_H[10]	7.593	33.770	-59.524	8.114	74.869
beta0_H[11]	9.897	49.631	-92.897	9.482	116.371
beta0_H[12]	6.594	9.986	-13.661	6.759	27.329
beta0_H[13]	9.699	9.934	-9.272	9.871	28.118
beta0_H[14]	6.991	11.407	-14.343	7.092	29.078
beta0_H[15]	4.565	105.391	-215.059	4.758	214.089
beta0_H[16]	8.240	31.325	-61.551	8.582	73.726